chore(resume): shelve Isovalent Data Engineer package (role pulled, ~86/100)

Finalized package retained for reuse; role closed (Cisco scrape 2026-06-02:
not on board, Recruitee link dead). PDFs/build artifacts gitignored.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>

output/Isovalent_DataEngineer/JD_isovalent_data_engineer.txt

@@ -0,0 +1,30 @@
+Senior Data Engineer, Observability — Isovalent (now part of Cisco)
+Location: Mountain View, Zurich, or Remote
+Org: Product and Engineering
+
+About Isovalent:
+Isovalent, founded by the creators of Cilium and eBPF, builds open-source software and
+enterprise solutions solving networking, security, and observability needs for modern
+cloud native infrastructure. Cilium is the choice of leading global organizations,
+including Adobe, AWS, Capital One, Datadog, GitLab, Google, and many more. Isovalent is
+now part of Cisco.
+
+The role / team:
+The team builds the observability capabilities of Cilium, Isovalent Load Balancer, and
+Tetragon — including data pipelines, storage, and analysis. You will build software to
+analyze customer environments to assess their security posture and implement
+recommendations. The platform collects observability data from Cilium using eBPF.
+
+Requirements:
+- M.Sc. in computer science or equivalent experience.
+- Experience working with remote teams and collaborating effectively in cross-functional teams.
+- Experience with Kubernetes, Cloud Native workloads, and distributed systems.
+- Desire to write beautiful and highly efficient code in Go.
+- Experience designing and/or implementing robust APIs (e.g. using gRPC).
+- Strong knowledge of SQL and database query optimization for large datasets.
+- Experience working with large, distributed, columnar databases for analytics workloads.
+- Knowledge of ClickHouse is a plus.
+
+Source: https://isovalent.com/careers/senior-data-engineer-observability-mountain-view-zurich-or-remote
+(JD reconstructed 2026-06-02 from official posting via search; page is JS-gated. Verify exact
+wording against the live posting before final submission.)

output/Isovalent_DataEngineer/critique_isovalent_data_engineer.md

@@ -0,0 +1,222 @@
+# Critique: Isovalent (Cisco) — Senior Data Engineer, Observability
+
+**Resume File:** `output/Isovalent_DataEngineer/e2e_isovalent_data_engineer_resume.tex`
+**Cover Letter:** `output/Isovalent_DataEngineer/e2e_isovalent_data_engineer_cover_letter.tex`
+**Date:** 2026-06-02
+**Score:** 84.5 / 100
+
+---
+
+## Domain-Specialist Lens
+
+### Reviewer Persona
+A Cilium/Isovalent senior engineer or eng manager on the observability team (Zurich hub, Thomas Graf's
+orbit). Deeply technical, open-source-native, reads CVs with a Go-and-ClickHouse mental template because
+that's the obvious-fit profile. Has seen many "I do data engineering" resumes that turn out to be dashboard
+BI work. Rolls eyes at buzzword padding and at anyone who clearly doesn't know what Hubble/Tetragon are.
+Genuinely impressed by: real distributed-systems-at-scale work, honest gap disclosure, and someone who has
+*operated* observability stacks under production pressure (most data-eng applicants have not).
+
+### Company Context
+Isovalent (creators of Cilium + eBPF, now Cisco) builds cloud-native networking/security/observability.
+This role builds the data backbone behind Hubble (network observability) and Tetragon (runtime-security
+observability): ingest high-volume eBPF telemetry → store in columnar analytics DBs (ClickHouse-class) →
+analyze customer security posture. Open-source-first culture (Cilium is CNCF-graduated). Success = scalable
+pipelines + fast analytical queries over very large telemetry datasets.
+
+### JD Vocabulary Extraction (ranked)
+| # | JD Term | Freq | Meaning at Isovalent | Resume Match? |
+|---|---------|------|----------------------|---------------|
+| 1 | data pipelines / storage / analysis | core | The actual job: telemetry ingest → store → analyze | YES (strong) |
+| 2 | columnar databases for analytics | high | ClickHouse-class OLAP over telemetry | PARTIAL (Teradata/Redshift/Impala, ClickHouse-transferable) |
+| 3 | SQL + query optimization for large datasets | high | Fast queries over high-cardinality telemetry | YES (strong) |
+| 4 | Kubernetes / cloud-native / distributed systems | high | The platform runs on K8s | YES (strong) |
+| 5 | Go (write efficient code) | high | Their implementation language | PARTIAL (learning; honest) |
+| 6 | robust APIs (e.g. gRPC) | med | Service interfaces | PARTIAL (REST/OpenAPI; no gRPC) |
+| 7 | ClickHouse | plus | Likely their store | PARTIAL (transferable framing) |
+| 8 | observability (security posture) | domain | The product domain | YES (Bosch stack — differentiator) |
+| 9 | remote / cross-functional teams | med | Distributed org | YES |
+| 10 | M.Sc. CS or equivalent | gate | Credential gate | YES (M.Eng., CS-adjacent) |
+
+### Domain Vocabulary Map
+| Resume Currently Says | Could Say for This JD | Why |
+|---|---|---|
+| "high-volume batch workloads" | "high-throughput / high-cardinality telemetry ingestion" | Their data is telemetry; cardinality is the OLAP pain point they live with |
+| "monitoring, alerting, telemetry" (skills) | already good — keep | Matches their domain exactly |
+| "ClickHouse-class columnar analytics (transferable...)" | keep — honest and correct | Right call; do not claim ClickHouse outright |
+
+### Gap Ranking
+- **Fatal:** None. This is one of the cleanest fits on the board — the role *is* data engineering for an analytics/observability platform.
+- **Serious:** Go (the obvious-fit candidate ships Go today); named ClickHouse. Both honestly bridged, not hidden.
+- **Cosmetic:** gRPC specifically; eBPF/Cilium internals (product knowledge, shown in CL not resume — correct).
+
+### Methodology Transfer Test
+| Achievement | How an Isovalent engineer sees it |
+|---|---|
+| Owned Fulfillment/Product Analysis ETL (Kafka→Teradata) | "Same ingest-pipeline ownership we need for eBPF telemetry." ✓ natural |
+| SQL/query optimization across Teradata/Redshift/Impala | "Directly the columnar-OLAP query work, just not on ClickHouse yet." ✓ natural |
+| Bosch observability stack (ELK/Grafana/Prometheus/Loki, 24/7) | "He's *run* observability under fire — rare; he knows what the data is for." ✓ strong |
+| ML inference on K8s into 24/7 fab | "Cloud-native distributed deployment discipline." ✓ natural |
+| Vizrt distributed real-time transcoding | "Distributed-systems chops at broadcast scale." ✓ natural |
+
+### Competitive Landscape
+- **Obvious-fit candidate:** Backend/data engineer from Datadog/Grafana Labs/Elastic with Go + ClickHouse on the CV.
+- **Our advantage:** Actually *operated* observability stacks in a high-stakes 24/7 setting; broad data-platform ownership across telco + semiconductor + broadcast; AWS cert; CH-based (Zurich hub fit).
+- **Their advantage:** Production Go; named ClickHouse; eBPF/kernel familiarity.
+
+---
+
+## Five-Perspective Read-Through
+
+### ATS Robot (keyword scan)
+| JD Keyword | Match |
+|---|---|
+| data pipelines / data platform | YES (verbatim, multiple) |
+| storage / columnar database | YES |
+| analysis / analytics | YES |
+| Kubernetes | YES |
+| cloud native | YES |
+| distributed systems | YES |
+| SQL | YES |
+| query optimization | YES |
+| large datasets | YES |
+| columnar / MPP / OLAP | YES |
+| ClickHouse | PARTIAL (ClickHouse-class) |
+| Go | PARTIAL (learning) |
+| APIs / gRPC | PARTIAL (REST APIs, OpenAPI; no gRPC) |
+| observability | YES (strong) |
+| monitoring / telemetry | YES |
+| cross-functional / remote | YES |
+| M.Sc. CS / equivalent | YES |
+| Kafka / Airflow | YES (bonus stack overlap) |
+| Grafana / Prometheus | YES |
+| Docker / CI/CD | YES |
+
+**Match rate:** ~17 strong + 3 partial / 20 ≈ **85% — PASS.** The three partials (Go, gRPC, ClickHouse) are deliberate honest bridges, not omissions.
+
+### Recruiter Glance (10 seconds)
+**Verdict: FORWARD.** Tagline reads "Senior Data Engineer | Pipelines · Columnar Analytics · Observability | Kubernetes · AWS · Python" — exact role language. Current title (Staff Data, Analytics & AI Engineer, Switzerland's largest telco) clears the bar instantly. CH-based + remote-DACH/EU line answers the location question in the header.
+
+### HR Screen (30 seconds)
+**Verdict: PHONE SCREEN.** Summary bridges cleanly (platform/pipelines + columnar + observability + honest Go note). Skills group names all signal target domain. First bullet under each position is the strongest JD-relevant one. 11+ years clears any seniority bar. Education (M.Eng. CS-adjacent) satisfies the M.Sc.-or-equivalent gate.
+
+### Hiring Manager (2 minutes)
+**Verdict: INTERVIEW.**
+**Top 3 observations:**
+1. "He has actually operated observability stacks (Grafana/Prometheus/Loki/ELK) 24/7 — not just built dashboards. That's the rare half of this role."
+2. "Columnar/SQL/query-optimization depth is real (Teradata/Redshift/Impala). ClickHouse is a short hop, and he says so honestly."
+3. "No Go in production — but he flags it openly and the systems instincts are there. Not a dealbreaker for a senior data hire."
+**Predicted first interview question:** "Walk me through how you'd design the ingestion + storage path for high-cardinality eBPF telemetry into a ClickHouse-class store, and where you'd expect query-optimization pain."
+
+### Technical Reviewer (10 minutes)
+**Truthfulness:** Mostly clean. **Two accuracy items to tighten (see Tier 1):**
+- Bullet 3 "Built a decentralized Data Mesh" reads as sole ownership of a company-wide platform; per KB the ODP/Data Mesh is a company-wide migration Dennis *contributed to* — he owns the modelling/build/onboarding of data products within it, not the Mesh itself. Hedge the platform verb.
+- Summary "I own Switzerland's largest telco's cloud-native data platform" is similarly broad; scope it to his pipelines/products/domains.
+- Go: "currently learning Go" must be literally true at submission time (per session note — verify or start the tutorial first).
+- gRPC correctly NOT claimed; ClickHouse correctly framed as transferable. C++ appropriately downplayed as legacy (per KB). Generali = Hamburg ✓, Bosch = Dresden ✓, education dates KB-correct ✓, languages = German/English only ✓.
+
+**Consistency:** CL ↔ resume aligned (same stack, same claims). CL "I built the Kafka ingestion pipelines / migrated..." traceable to bullets 1–2. Same Data-Mesh scoping caveat applies to the CL "I own the cloud-native data platform behind our Fulfillment and Product Analysis domains" — the CL is actually better-scoped ("behind our ... domains") than the resume summary; align the summary to match.
+
+---
+
+## Eight-Dimension Scoring
+
+| Dimension | Score | Weight | Weighted | Notes |
+|---|---|---|---|---|
+| ATS Keywords | 9.0/10 | 15% | 1.35 | ~85% match; Go/gRPC/ClickHouse honest partials |
+| Summary | 8.5/10 | 10% | 0.85 | Strong bridge; scope the "I own ... the platform" claim |
+| Skills Section | 9.0/10 | 10% | 0.90 | Excellent group names; ClickHouse-class framing is right |
+| Bullet Quality | 8.0/10 | 25% | 2.00 | Strong alignment; Data-Mesh overclaim + Security Champion weakest + -ing pattern density |
+| Publications/Credentials | 8.0/10 | 10% | 0.80 | N/A pubs (resume); certs strong (AWS SAA active, Udacity DE, iSAQB) |
+| Narrative Coherence | 8.5/10 | 15% | 1.275 | Clean platform+observability+distributed thread across all roles |
+| Page Fill & Visual | 7.5/10 | 5% | 0.375 | Clean 2pp compile; Bosch header date wraps; pg2 ~75% (OK) |
+| Credibility Signals | 8.5/10 | 10% | 0.85 | Telco + Bosch + Vizrt(CNN/BBC) + AWS cert + Staff level |
+| **Total** | | **100%** | **84.5** | Strong; 2–3 fixes → ~87 |
+
+---
+
+## Interview Likelihood
+
+| Reader | Probability | Key Factor |
+|--------|------------|------------|
+| ATS | 95% | ~85% keyword match, all core terms present |
+| Recruiter (10s) | 90% | Title + tagline + CH-location all on-target |
+| HR (30s) | 88% | Summary bridge + group names + seniority |
+| Hiring Manager (2m) | 70% | Observability-operator angle is the differentiator; Go gap is the discount |
+| Technical Panel (10m) | 65% | Real columnar/SQL/distributed depth; ClickHouse/Go are interview-stage probes |
+
+**Ceiling:** Current 84.5 → with Tier 1 applied ~87 → hard ceiling ~88–89 (structural: no production Go / no named ClickHouse caps the "obvious-fit" parity; only real Go shipping or a ClickHouse project closes it).
+
+---
+
+## Actionable Improvements
+
+### Tier 1 (HIGH — do these)
+1. **Fix Data-Mesh ownership claim (accuracy).** Bullet 3 currently: *"Built a decentralized Data Mesh with governed data products and metadata management on AWS..."* → reframe to own what he actually owns: e.g., *"Built governed data products and metadata management within Swisscom's company-wide Data Mesh on AWS (Glue, Athena, CloudFormation, CI/CD), making them discoverable for downstream teams to query directly."* Owns the products/modelling, not the whole Mesh. (Accuracy > all; per `[[feedback_swisscom_datamesh_ownership]]`.) **+1.0**
+2. **Scope the summary "own" claim.** *"I own Switzerland's largest telco's cloud-native data platform on AWS..."* → *"I build and own cloud-native data pipelines and products on Switzerland's largest telco's AWS platform..."* Aligns with the better-scoped CL phrasing and the Component-Owner reality. **+0.5**
+3. **Verify "currently learning Go" is literally true** before submission (start a Go tutorial/project if not). Honest-gap framing only works if it's true; an Isovalent interviewer may ask "what are you working through in Go right now?" **Blocking accuracy gate, not a score delta.**
+
+### Tier 2 (MEDIUM — optional)
+1. **Fix Bosch header line-wrap (visual).** The title *"Observability, Production ML & Data Services in 24/7 Semiconductor Manufacturing"* pushes the date onto a second line. Shorten to e.g. *"Observability, Production ML & Data Services — 24/7 Semiconductor Fab"* so the date sits on one line. **+0.3**
+2. **Reconsider the Security Champion bullet (SW-7).** It's the weakest bullet for a pure data-eng read and per KB it's a team role, not an achievement. *Counter-argument:* this JD is literally about assessing "security posture," so DevSecOps color is mildly on-thesis here — defensible to keep. If kept, it's fine; if you want a tighter top-of-resume, drop it and let Swisscom run 6 bullets. Judgment call. **+0.3 if dropped**
+3. **One telemetry-vocabulary swap.** Bullet 5 "high-volume batch workloads" → "high-throughput ingestion" reads more like their world (telemetry, not batch ETL). **+0.2**
+
+### Tier 3 (COSMETIC — skip)
+1. Reduce trailing participial-clause ("…enabling/giving/owning/extending X") density — ~8 of 19 bullets follow it; vary 2–3 to break the rhythm (mild AI-fingerprint signal, but most end in concrete nouns so low priority).
+2. Summary "AWS Solutions Architect" → "AWS Certified Solutions Architect" (avoid reading as a self-title).
+3. Triplet-list density ("X, Y and Z") is a touch high; not worth editing on a resume.
+
+**Verdict:** Apply Tier 1 (esp. #1 — it's an accuracy fix, not a style one). Tier 2 #1 (header wrap) is a quick visual win. Everything else is optional.
+
+---
+
+## Interview Bridge Points
+
+| Resume Topic | Target Equivalent | Opening Line |
+|---|---|---|
+| Bosch observability stack (ELK/Grafana/Prometheus/Loki, 24/7) | Hubble/Tetragon telemetry pipeline | "I've run the consumer side of observability under 24/7 production pressure — building the platform that emits it is the same problem from the other end." |
+| Teradata/Redshift/Impala SQL + query optimization | ClickHouse-class OLAP over telemetry | "Columnar query optimization transfers directly; with ClickHouse I'd be learning the engine's quirks, not the discipline." |
+| Kafka → Teradata ETL ownership | eBPF telemetry ingestion | "Same ingest-pipeline ownership — high-throughput source, schema governance, SLA on freshness." |
+| ML inference on K8s into 24/7 fab | Cloud-native distributed deployment | "I've shipped containerized workloads into environments with zero maintenance windows; that operational bar matches yours." |
+| Vizrt distributed real-time transcoding | Distributed-systems at scale | "Real-time distributed backends for CNN/BBC taught me the latency and failure-mode thinking telemetry pipelines need." |
+| No production Go (honest) | Their implementation language | "I haven't shipped Go yet, but I've written performance-sensitive Python and C++; I'm working through Go now and the systems instincts carry over." |
+| AWS lakehouse migration (S3/Glue/Athena/Iceberg/Redshift) | Cloud-native storage layer | "I led the legacy-to-lakehouse move for my domains — exactly the storage-layer evolution a telemetry platform goes through." |
+
+---
+
+## Part 6: Cover Letter Critique (Industry)
+
+**6A Anti-Patterns:** ✓ Opens with a Cilium/eBPF-specific hook, not "I am writing to express." ✓ Names Cilium/Hubble/Tetragon/CNCF. ✓ Clear "why Isovalent" (open-source-first, CNCF-graduated, CH hub). ✓ Strongest qual in P1. ✓ Go gap handled confidently, not apologetically. ✓ Active CTA close. No CV-bullet rehash — adds narrative.
+**6B Tailoring:** ✓ Names products + CNCF + Zurich hub. ✓ Supplemental JD terms (eBPF, security posture, telemetry, CNCF). ✓ Proposes the connection (operated observability → build the platform behind it).
+**6C Industry checks:** ✓ Business-value translation ("fast answers about a customer's security posture"). ✓ No "leaving academia." ✓ Jargon level appropriate (insiders read it).
+**6D ATS:** ~7 high-priority JD terms present (pipelines, columnar, SQL/query optimization, Kubernetes, observability, telemetry, ClickHouse-class). Good.
+**6E Structural:** Word count ~300 (top of industry 250–300 band — fine). Tone results-driven. ~5 quantified/concrete claims. Sentence-length variety good ("Someone has to build…" short vs long appositive sentences). **Zero em-dashes** (uses comma appositives — compliant).
+**6F Package cohesion:** ✓ Resume stands alone. ✓ CL deepens (motivation + product knowledge), doesn't introduce new achievements. ✓ No date/metric contradictions. Note: CL "I built the Kafka ingestion pipelines / migrated a legacy Teradata and Oracle warehouse" — keep consistent with the Tier-1 Data-Mesh scoping; the CL's domain-scoped phrasing is already the safer model for the resume to follow.
+
+---
+
+## Part 6G: AI Fingerprint Scan
+1. Tier-1 banned words: **none** (no leverage/utilize/spearhead/robust/foster/delve). ✓
+2. Banned phrases: **none** (no "proven track record", "passionate about", "well-versed"). ✓
+3. Em-dashes (`---`): resume uses `--` en-dashes only; CL uses commas. **0 em-dashes.** ✓
+4. Bullet -ing endings: ~8/19 bullets end in a participial clause ("…enabling/giving/owning/extending X"), but **most terminate on a concrete noun** (workloads, team, partners, downtime), not a vague abstraction. Borderline; flagged Tier 3 to vary 2–3.
+5. 3+ consecutive same-length sentences (CL): no — varied. ✓
+6. Repeated paragraph-start structure (CL): P1 "Cilium…", P2 "At Swisscom…", P3 "Before Swisscom…", P4 "What draws me…" — varied. ✓
+7. Triplet density: a touch high but acceptable for a resume. Minor.
+8. CL generic opener: no — company-specific. ✓
+9. Metaphorical landscape/journey/realm: none. ✓
+10. Passive-voice bullets: low (<10%); strong active verbs. ✓
+11. Honors `---` vs `. `: Certs use `\item` bullets with `. ` — ✓.
+12. Banned adverbs (meticulously/notably/subsequently): none. ✓
+**Result: PASS** — no Tier-1 fingerprint failures. Only the participial-clause density (item 4) noted as low-priority polish.
+
+---
+
+## Part 7: Post-Generation Verification
+**Mechanical:** ✓ All bullets within char limits (24/24 OK or NEAR-MAX, none OVER). ✓ Orphan check passes. ✓ 2 pages, page 2 ~75% filled (within budget). ✓ No ordering errors.
+**Content:** ✓ ATS ≥70%. ⚠ Provenance: Data-Mesh "Built" overclaim (Tier 1 #1). ✓ No forbidden terms (no LangChain; no French/Italian; Security Champion framed as team role 2025/26, not award). ✓ No gRPC/Go fabrication. ✓ C++ downplayed.
+**Structural:** ✓ "Isovalent" / "Cisco" spelled correctly. ✓ Complete preambles, both compile standalone clean via MiKTeX. ✓ Date format consistent. ✓ Email dennis@thiessen.io correct. ✓ Page count = 2 (resume), 1 (CL). ⚠ Bosch header date-wrap (Tier 2 #1).
+
+---
+
+*End of critique. Score: 84.5/100 — strong, submit-ready after the two accuracy tightenings (Tier 1 #1 and #2) and the Go-truth check.*

output/Isovalent_DataEngineer/e2e_isovalent_data_engineer_cover_letter.tex

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+\documentclass[11pt,a4paper,roman]{moderncv}
+\usepackage[english]{babel}
+\moderncvstyle{classic}
+\moderncvcolor{blue}
+\usepackage[utf8]{inputenc}
+\usepackage[T1]{fontenc}
+\usepackage{lmodern}
+\usepackage{ragged2e}
+\usepackage[scale=0.79]{geometry}
+\usepackage[version=4,arrows=pgf-filled]{mhchem}
+\renewcommand*{\makeletterclosing}{\par\vspace{2ex}\closingname\par}
+
+% ========== PERSONAL INFO ==========
+\name{Dennis}{Thiessen}
+\address{Bern, Switzerland}
+\phone[mobile]{+41 795 955 585}
+\email{dennis@thiessen.io}
+% ======================================
+
+\begin{document}
+
+\recipient{To}{Hiring Team\\Senior Data Engineer, Observability\\Isovalent (part of Cisco)\\Zurich, Switzerland}
+\date{\today}
+\opening{Dear Isovalent Hiring Team,}
+\makelettertitle
+
+\begin{justify}
+Cilium turned eBPF into the data plane for cloud-native networking, and Hubble and Tetragon now emit a firehose of network and runtime-security telemetry on top of it. Someone has to build the pipelines and columnar stores that turn that stream into fast answers about a customer's security posture. That is the data engineering I have done for a decade, which is why I am applying for your Senior Data Engineer, Observability role.
+
+At Swisscom, Switzerland's largest telco, I own the cloud-native data platform behind our Fulfillment and Product Analysis domains. I built the Kafka ingestion pipelines, migrated a legacy Teradata and Oracle warehouse to an AWS lakehouse (S3, Glue, Athena/Iceberg, Redshift, Airflow), and run our Python data services on Kubernetes with GitLab CI/CD. Most of my week is SQL and query optimization over large columnar stores, Teradata, Redshift and Impala, the exact work ClickHouse-class analytics at your telemetry volumes demands.
+
+Before Swisscom I ran the observability side of this equation. At a Bosch 300mm fab I designed and operated a centralized stack, ELK with Kafka ingestion plus Grafana, Prometheus and Loki, for anomaly detection across 24/7 production with no maintenance windows. I also tuned data services over Hadoop/Impala for defect analysis, and earlier engineered distributed real-time transcoding backends at Vizrt for broadcasters like CNN and the BBC. I have not shipped Go in production yet, but the systems and performance instincts it rewards are ones I have practiced for years, and I am learning it now.
+
+What draws me to Isovalent specifically is the open-source-first culture, Cilium being CNCF-graduated rather than a closed product, and the fact that the founding team built a real engineering hub here in Switzerland, where I am based. I would be glad to walk through the data backbone I would build behind Hubble and Tetragon whenever suits your team.
+\end{justify}
+
+\vspace{0.3cm}
+{Sincerely,\\
+Dennis Thiessen, M.Eng.\\
+Staff Data, Analytics \& AI Engineer\\
+Swisscom (Schweiz) AG}
+
+\end{document}

output/Isovalent_DataEngineer/e2e_isovalent_data_engineer_resume.tex

@@ -0,0 +1,164 @@
+\documentclass{resume}
+\usepackage{hyperref}
+\usepackage{enumitem}
+\usepackage{fontawesome}
+\usepackage{tikz}
+\usepackage{graphicx}
+\hypersetup{
+    colorlinks = true,
+    linkcolor = [rgb]{0.9,0.4,0.4},
+    anchorcolor = [rgb]{0.9,0.4,0.4},
+    citecolor = [rgb]{0.4,0.4,0.4},
+    filecolor = [rgb]{0.4,0.4,0.4},
+    urlcolor = [rgb]{0.0,0.0,0.99},
+}
+\usepackage{xcolor}
+\usepackage[utf8]{inputenc}
+\usepackage[T1]{fontenc}
+\usepackage{lmodern}
+\usepackage[version=4,arrows=pgf-filled]{mhchem}
+\usepackage[includefoot,left=0.5in,top=0.5in,right=0.5in,bottom=0.2in,textwidth=7.5in,textheight=10.8in]{geometry}
+\usepackage{fancyhdr}
+\pagestyle{fancy}
+\fancyhf{}
+\renewcommand{\headrulewidth}{0pt}
+\fancyfoot[R]{\hfill \thepage/\pageref{LastPage}}
+\newcommand{\tab}[1]{\hspace{.2667\textwidth}\rlap{#1}}
+\newcommand{\itab}[1]{\hspace{0em}\rlap{#1}}
+
+%----------------------------------------------------------------------------------------
+%	HEADER
+%----------------------------------------------------------------------------------------
+\name{Dennis Thiessen, M.Eng.}
+\address{\href{https://linkedin.com/in/dennis-thiessen}{LinkedIn}}
+\address{dennis@thiessen.io \\ +41 795 955 585}
+\address{Bern, Switzerland $\vert$ German citizen $\vert$ Available remote across DACH/EU/UK}
+\address{{Senior Data Engineer $\vert$ Pipelines $\cdot$ Columnar Analytics $\cdot$ Observability $\vert$ Kubernetes $\cdot$ AWS $\cdot$ Python}}
+
+
+\begin{document}
+
+\vspace{-0.15cm}
+
+%----------------------------------------------------------------------------------------
+%	SUMMARY
+%----------------------------------------------------------------------------------------
+\begin{rSection}{Summary}
+Data engineer with 11+ years building production data platforms and pipelines at scale. I build and own cloud-native data pipelines and products on Switzerland's largest telco's \textbf{AWS} platform (\textbf{Kafka}, \textbf{Airflow}, \textbf{Redshift}, PySpark, \textbf{Kubernetes}, GitLab CI/CD), with deep \textbf{SQL} and query optimization across Teradata, Redshift and Impala columnar stores. Built and operated full \textbf{observability} stacks (\textbf{Grafana}, \textbf{Prometheus}, Loki, ELK) for a 24/7 Bosch semiconductor fab, and engineered distributed real-time backends at Vizrt for CNN, BBC and Al Jazeera. \textbf{Python} expert and polyglot (Java, C++); AWS Solutions Architect; currently learning \textbf{Go}.
+\end{rSection}
+\vspace{-0.15cm}
+
+%----------------------------------------------------------------------------------------
+%	TECHNICAL SKILLS — Format C, 5 groups (4-3-2-2-2)
+%----------------------------------------------------------------------------------------
+\begin{rSection}{Technical Skills}
+
+\begin{skillgroup}{Data Engineering \& Distributed Systems}
+\skilldash{\textbf{Kafka}, \textbf{Airflow}, \textbf{PySpark} / Apache Spark, Apache Iceberg, Hadoop / ImpalaSQL, ETL/ELT pipeline design}
+\skilldash{\textbf{SQL} (Oracle $\cdot$ Teradata $\cdot$ Impala $\cdot$ Postgres), query optimization, data modeling, partitioning, indexing}
+\skilldash{High-throughput ingestion pipelines, batch and stream processing, distributed systems, data lakehouse}
+\skilldash{Data Mesh, data products, metadata management, data catalog, data governance, SLA / on-call ownership}
+\end{skillgroup}
+
+\begin{skillgroup}{Cloud-Native Infrastructure \& Observability}
+\skilldash{\textbf{Kubernetes}, \textbf{Docker}, Ansible, GitLab CI/CD, Jenkins, Infrastructure as Code, serverless, DevSecOps}
+\skilldash{\textbf{AWS} (S3, Glue, Athena/Iceberg, \textbf{Redshift}, Lambda, Step Functions, \textbf{Airflow}, CloudFormation)}
+\skilldash{\textbf{Grafana}, \textbf{Prometheus}, Loki, ELK Stack (Elasticsearch, Logstash, Kibana), monitoring, alerting, telemetry}
+\end{skillgroup}
+
+\begin{skillgroup}{Columnar \& Analytical Databases}
+\skilldash{\textbf{Teradata}, \textbf{Redshift}, Hadoop / Impala (MPP / columnar OLAP), OracleDB, large-dataset query tuning}
+\skilldash{ClickHouse-class columnar analytics (transferable from Teradata / Redshift / Impala), data warehouse modeling}
+\end{skillgroup}
+
+\begin{skillgroup}{Programming Languages \& APIs}
+\skilldash{\textbf{Python} (expert), \textbf{Java} (strong), SQL, JavaScript / TypeScript, Bash; \textbf{Go} (learning)}
+\skilldash{REST APIs, FastAPI / Flask, Express.js, OpenAPI; C++ (Vizrt, legacy), C\# / .NET (Bosch / Fraunhofer, legacy)}
+\end{skillgroup}
+
+\begin{skillgroup}{Certifications}
+\skilldash{\textbf{AWS Certified Solutions Architect -- Associate} (active until Sep 2027), Data Engineering with AWS (Udacity)}
+\skilldash{iSAQB CPSA -- Foundation Level (software architecture), ITIL Foundation; Security Champion (DevSecOps, 2025/26)}
+\end{skillgroup}
+
+\end{rSection}
+\vspace{-0.15cm}
+
+%----------------------------------------------------------------------------------------
+%	PROFESSIONAL EXPERIENCE
+%----------------------------------------------------------------------------------------
+\begin{rSection}{Professional Experience}
+
+% --- Swisscom (Oct 2023 -- Present) — 6 bullets: SW-2, SW-1, SW-7, SW-3, SW-6, SW-4 ---
+\begin{rSubsection}{Cloud-Native Data Platform, Pipelines \& Observability at Telecom Scale}{\textcolor{black!60}{Oct 2023 -- Present}}{Staff Data, Analytics \& AI Engineer, Swisscom (Schweiz) AG}{Bern, Switzerland}
+\item Owned Fulfillment and Product Analysis ETL pipelines (Oracle, \textbf{Kafka} to Teradata in \textbf{Python}) as Component Owner, enforcing data governance and SLA compliance for business-critical, telecom-scale data flows.
+\item Migrated the legacy Teradata/Oracle ETL stack to cloud-native \textbf{AWS} (S3, Glue, \textbf{Airflow}, Athena/Iceberg, \textbf{Redshift}, CloudFormation IaC), enabling scalable serverless processing for analytics and ML workloads.
+\item Built governed data products and metadata management within Swisscom's company-wide Data Mesh on \textbf{AWS} (Glue, Athena, CloudFormation, CI/CD), making them discoverable for downstream teams to query directly.
+\item Designed, deployed and operate \textbf{Python} data services on \textbf{Kubernetes} with GitLab CI/CD automation, owning containerized delivery from build and test through production rollout in an agile DevOps team.
+\item Applied \textbf{PySpark} and distributed computing across the Swisscom Data Lake to process large-scale datasets, extending \textbf{Python} and \textbf{SQL} pipelines to high-volume batch workloads for Fulfillment and Product Analysis.
+\item Delivered data products, analyses and dashboards for B2B stakeholders, and drove \textbf{Python} automation of recurring workflows plus 3rd-level root cause analysis under on-call duty to keep the platform reliable.
+\item Hold the team's Security Champion role (2025/26), owning DevSecOps compliance, risk monitoring and deviation tracking for the data platform, with 100h of annual cloud-security and security-by-design training.
+\end{rSubsection}
+
+% --- Bosch (Feb 2020 -- Dec 2022) — 4 bullets: BS-4, BS-2, BS-1, BS-3 ---
+\begin{rSubsection}{Observability, Production ML \& Data Services in 24/7 Semiconductor Manufacturing}{\textcolor{black!60}{Feb 2020 -- Dec 2022}}{(Senior) Data Engineer, Robert Bosch Semiconductor Manufacturing}{Dresden, Germany}
+\item Designed and ran a centralized \textbf{observability} stack (ELK with \textbf{Kafka} ingestion, \textbf{Grafana} dashboards, \textbf{Prometheus} metrics, Loki logs) for anomaly detection and monitoring across 24/7 semiconductor production.
+\item Built data services in \textbf{Python}, Java and C\# over OracleDB and Hadoop/ImpalaSQL, optimizing query performance over large analytics datasets for semiconductor defect-management and process-optimization teams.
+\item Containerized and orchestrated \textbf{ML inference} (\textbf{Docker}, \textbf{Kubernetes}, Ansible) into Bosch's 24/7 fab, automating image-based defect classification across 300mm wafer lines with no production downtime.
+\item Served as Application Owner for the semiconductor analytics suite and upstream pipelines, defining SLOs, managing vendors, and delivering training and docs across cross-functional fab operations teams.
+\end{rSubsection}
+
+% --- Fraunhofer (Sep 2018 -- Oct 2019) — 3 bullets: FC-3, FC-1, FC-2 ---
+\begin{rSubsection}{Microservice Engineering \& Applied Data Research}{\textcolor{black!60}{Sep 2018 -- Oct 2019}}{Research Software Engineer, Fraunhofer-Center for Maritime Logistics CML}{Hamburg, Germany}
+\item Built microservices and \textbf{REST APIs} (Express.js, \textbf{Docker}, SQLite) for MISSION, a Fraunhofer maritime data-exchange platform, enabling structured data interchange across ports, operators and research partners.
+\item Independently set up the team's first Jenkins CI/CD pipeline with quality gates and build automation, and developed the SCEDAS crew-scheduling system (C\#, .NET, MS SQL Server, Entity Framework).
+\item Contributed \textbf{ML} and NLP components to ARTUS, a Fraunhofer research project for automatic sea-rescue speech transcription, applying speech recognition and machine learning in a safety-critical maritime domain.
+\end{rSubsection}
+
+% --- Vizrt (Jul 2017 -- May 2018) — 2 bullets: VZ-1, VZ-2 ---
+\begin{rSubsection}{Distributed Real-Time Backend Engineering at Broadcast Scale}{\textcolor{black!60}{Jul 2017 -- May 2018}}{DevOps Engineer, Vizrt}{Bergen, Norway}
+\item Engineered distributed real-time video transcoding backend components in \textbf{Python} (with legacy C++ modules) for Vizrt's broadcast platform, serving global media customers including CNN, BBC and Al Jazeera.
+\item Built an automated integration and unit test suite for A/V streaming in \textbf{Python} and integrated quality gates into the CI/CD pipeline, which shortened the feedback loop and raised release quality.
+\end{rSubsection}
+
+% --- Generali (May 2015 -- Jun 2017) — 2 bullets: GN-1, GN-3 ---
+\begin{rSubsection}{Test Automation, CI/CD \& Java Backend}{\textcolor{black!60}{May 2015 -- Jun 2017}}{IT Consultant, Generali Deutschland Informatik Services}{Hamburg, Germany}
+\item Introduced BDD test automation at Generali (Serenity-BDD, Selenium, JBehave), running the initial PoC and taking technical ownership, then trained teams and presented the methodology to the Java Community.
+\item Pioneered UIPath RPA at Generali GDIS, building PoCs and serving as internal RPA contact for group companies, extending automation from test tooling into business process automation.
+\item Developed Java/J2EE features for the PIA-Postkorb workflow portal, migrated WebServices to the XLDeploy process, and contributed to an Apache Camel / Spring Boot dispatcher integration PoC.
+\end{rSubsection}
+
+
+\end{rSection}
+\vspace{-0.15cm}
+
+%----------------------------------------------------------------------------------------
+%	EDUCATION — FIXED (dates per KB correction: B.Eng Oct 2009--Oct 2012, M.Eng Apr 2012--Oct 2013)
+%----------------------------------------------------------------------------------------
+\begin{rSection}{Education}
+{M.Eng.\ Computer Aided Engineering (Software Design \& Engineering)} \hfill {\textcolor{black!60}{Apr 2012 -- Oct 2013}}\\
+{Universit\"at der Bundeswehr M\"unchen}; thesis at Tongji University, Shanghai \hfill Thesis Grade: \textbf{1.0}\\
+{\small Thesis: \textit{Development of a Web-Based Remote Fault Diagnosis System} (Neural Networks, PSO, Fuzzy Logic)}
+
+{B.Eng.\ Information and Telecommunication Technologies} \hfill {\textcolor{black!60}{Oct 2009 -- Oct 2012}}\\
+{Universit\"at der Bundeswehr M\"unchen}, Munich, Germany
+\end{rSection}
+\vspace{-0.15cm}
+
+%----------------------------------------------------------------------------------------
+%	CERTIFICATIONS & AWARDS — FIXED
+%----------------------------------------------------------------------------------------
+\begin{rSection2}{Certifications \& Awards}
+\item \textbf{AWS Certified Solutions Architect -- Associate}, Amazon Web Services (2024, active until Sep 2027).
+\item \textbf{Data Engineering with AWS Nanodegree}, Udacity (2026). AWS data pipeline architecture.
+\item \textbf{iSAQB CPSA -- Foundation Level}, iSAQB (2016). Certified Professional for Software Architecture.
+\item \textbf{ITIL Foundation Certificate in IT Service Management}, PEOPLECERT / AXELOS (2016).
+\item \textbf{IBM AI Engineering Specialization}, Coursera. Deep learning, TensorFlow, Keras, Apache Spark ML.
+\end{rSection2}
+
+\begin{center}
+\vspace{0.1cm}
+\textit{Languages: German (native), English (fluent)}
+\end{center}
+
+\end{document}

output/Isovalent_DataEngineer/resume.cls

@@ -0,0 +1,199 @@
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% Medium Length Professional CV - RESUME CLASS FILE
+%
+% This template has been downloaded from:
+% http://www.LaTeXTemplates.com
+%
+% This class file defines the structure and design of the template. 
+%
+% Original header:
+% Copyright (C) 2010 by Trey Hunner
+%
+% Copying and distribution of this file, with or without modification,
+% are permitted in any medium without royalty provided the copyright
+% notice and this notice are preserved. This file is offered as-is,
+% without any warranty.
+%
+% Created by Trey Hunner and modified by www.LaTeXTemplates.com
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+\ProvidesClass{resume}[2018/09/25 v1.0 Resume class]  
+
+\LoadClass[10pt, a4paper]{article} % Font size and paper type
+\usepackage{lastpage}
+\usepackage[parfill]{parskip} % Remove paragraph indentation
+\usepackage{array} % Required for boldface (\bf and \bfseries) tabular columns
+\usepackage{ifthen} % Required for ifthenelse statements
+\usepackage{enumitem}
+ \pagestyle{empty} % Suppress page numbers
+
+%----------------------------------------------------------------------------------------
+%	HEADINGS COMMANDS: Commands for printing name and address
+%----------------------------------------------------------------------------------------
+
+\def \name#1{\def\@name{#1}} % Defines the \name command to set name
+\def \@name {} % Sets \@name to empty by default
+
+\def \addressSep {$|$} % Set default address separator to a diamond
+
+% One, two or three address lines can be specified 
+\let \@addressone \relax
+\let \@addresstwo \relax
+\let \@addressthree \relax
+\let \@addressfour \relax
+
+% \address command can be used to set the first, second, and third address (last 2 optional)
+\def \address #1{
+  \@ifundefined{@addresstwo}{
+    \def \@addresstwo {#1}
+  }{
+  \@ifundefined{@addressthree}{
+  \def \@addressthree {#1}
+  }{
+  \@ifundefined{@addressfour}{
+  \def \@addressfour {#1}
+  } {\def \@addressone {#1}
+  }
+     
+  }
+  }
+}
+
+% \printaddress is used to style an address line (given as input)
+\def \printaddress #1{
+  \begingroup
+    \def \\ {\addressSep\ }
+             {#1}
+%    \centerline{#1}
+  \endgroup
+  \par
+ % \addressskip
+}
+
+% \printname is used to print the name as a page header
+\def \printname {
+  \begingroup
+  % \MakeUppercase
+  {\namesize\bf \@name} \hfil
+%    \hfil{\MakeUppercase{\namesize\bf \@name}}\hfil
+    \nameskip\break
+  \endgroup
+}
+
+%----------------------------------------------------------------------------------------
+%	PRINT THE HEADING LINES
+%----------------------------------------------------------------------------------------
+
+\let\ori@document=\document
+\renewcommand{\document}{
+  \ori@document  % Begin document
+  % \begin{center}
+  \printname % Print the name specified with \name
+  \@ifundefined{@addressone}{}{ % Print the first address if specified
+    \printaddress{\@addressone}}
+  \@ifundefined{@addresstwo}{}{ % Print the second address if specified
+    \printaddress{\@addresstwo}}
+     \@ifundefined{@addressthree}{}{ % Print the third address if specified
+    \printaddress{\@addressthree}}
+     \@ifundefined{@addressfour}{}{ % Print the third address if specified
+    \printaddress{\@addressfour}}
+    
+    % \end{center}
+}
+
+%----------------------------------------------------------------------------------------
+%	SECTION FORMATTING
+%----------------------------------------------------------------------------------------
+
+% Defines the rSection environment for the large sections within the CV
+\newenvironment{rSection}[1]{ % 1 input argument - section name
+   \sectionskip
+   {\bf #1}
+%   \MakeUppercase{\bf #1} % Section title
+   \sectionlineskip
+  \hrule % Horizontal line
+  \begin{list}{}{ % List for each individual item in the section
+    \setlength{\leftmargin}{0.50em} % Margin within the section
+  }
+  \item[]
+}{
+  \end{list}
+}
+
+\newenvironment{rSection2}[1]{ % 1 input argument - section name
+  \sectionskip
+  {\bf #1} % Section title
+  \sectionlineskip
+  \hrule % Horizontal line
+  \medskip
+  \begin{list}{$\bullet$}{\setlength{\leftmargin}{1.5em}}
+   \itemsep -0.3em \vspace{-0.5em} % Compress items in list together for aesthetics
+}{
+  \end{list}
+ \vspace{0.5em}
+}
+
+\newenvironment{rSection3}[1]{ % 1 input argument - section name
+  \sectionskip
+  {\bf #1} % Section title
+  \sectionlineskip
+  \hrule % Horizontal line
+  \medskip
+  \begin{enumerate}[]{\setlength{\leftmargin}{1.5em}}
+   \itemsep -0.3em \vspace{-0.5em} % Compress items in list together for aesthetics
+}{
+  \end{enumerate}
+ \vspace{0.5em}
+}
+%----------------------------------------------------------------------------------------
+%	WORK EXPERIENCE FORMATTING
+%----------------------------------------------------------------------------------------
+
+\newenvironment{rSubsection}[4]{ % 4 input arguments - company name, year(s) employed, job title and location
+ {\bf #1} \hfill {#2} % Bold company name and date on the right
+ \ifthenelse{\equal{#3}{}}{}{ % If the third argument is not specified, don't print the job title and location line
+  \\
+  {\em #3} \quad {\em #4} % Italic job title and location
+  }\smallskip
+  \begin{list}{$\cdot$}{\leftmargin=1.5em} % \cdot used for bullets, no indentation
+   \itemsep -0.2em \vspace{-0.2em} % Compress items in list together for aesthetics
+  }{
+  \end{list}
+  \vspace{0.2 em} % Some space after the list of bullet points
+}
+
+
+
+%----------------------------------------------------------------------------------------
+%	FORMAT C SKILLS COMMANDS
+%----------------------------------------------------------------------------------------
+
+% Skills group environment: \begin{skillgroup}{Group Name} ... \end{skillgroup}
+% Renders bold header + indented dash sub-items. Each \skilldash = exactly 1 rendered line.
+\newenvironment{skillgroup}[1]{%
+  \textbf{#1}\par\nopagebreak%
+  \vspace{-\parskip}%
+  \begin{list}{--}{\leftmargin=0.8em \labelsep=0.3em \itemsep=0pt \topsep=0.1em \parsep=0pt \partopsep=0pt}%
+}{%
+  \end{list}%
+  \vspace{-\parskip}\vspace{0.45em}%
+}
+
+% Single dash sub-item within a skillgroup. Content must fit 1 rendered line.
+% Char limit: 119 - (0.5 x bold_char_count) at 10pt
+\newcommand{\skilldash}[1]{\item #1}
+
+%----------------------------------------------------------------------------------------
+%	EXPERIENCE SUB-THEME COMMAND
+%----------------------------------------------------------------------------------------
+
+% Sub-theme underline header within rSubsection
+\newcommand{\subtheme}[1]{\item[] \underline{#1}}
+
+% The below commands define the whitespace after certain things in the document - they can be \smallskip, \medskip or \bigskip
+\def\namesize{\huge} % Size of the name at the top of the document
+\def\addressskip{\smallskip} % The space between the two address (or phone/email) lines
+\def\sectionlineskip{\medskip} % The space above the horizontal line for each section 
+\def\nameskip{\medskip} % The space after your name at the top
+\def\sectionskip{\medskip} % The space after the heading section

output/Isovalent_DataEngineer/session_isovalent_data_engineer.md

@@ -0,0 +1,180 @@
+# Session: Isovalent (Cisco) — Senior Data Engineer, Observability
+
+**Status:** Phase 0: DONE — awaiting user confirmation before Phase 1
+**Created:** 2026-06-02
+**JD source:** `output/Isovalent_DataEngineer/JD_isovalent_data_engineer.txt`
+**Output folder:** `output/Isovalent_DataEngineer/`
+
+## JD Info
+- **Role:** Senior Data Engineer, Observability
+- **Company:** Isovalent (creators of Cilium + eBPF; now part of Cisco)
+- **Location:** Mountain View, Zurich, or Remote → CH-based / Europe-remote, works from Bern. DIRECT match.
+- **Bundle (primary):** Staff / Senior Data Engineer (`bundle_data_engineer.md`)
+- **Bundle (secondary):** Data Platform / Infra (`bundle_data_platform.md`) — for K8s / cloud-native / distributed-systems bridge
+- **Format:** Resume (2-page, resume.cls) + 1-page cover letter
+- **Salary/Details:** Not posted. Cisco/Isovalent CH eng band ~CHF 180–250k+ — clears comp bar.
+
+## JD Analysis
+
+### Requirements
+| # | Requirement | Match | Evidence |
+|---|-------------|-------|----------|
+| 1 | M.Sc. CS or equivalent | DIRECT | M.Eng. Computer Aided Engineering (Software Design & Engineering), Univ. der Bundeswehr München |
+| 2 | Remote teams + cross-functional collaboration | DIRECT | Swisscom Component Owner across Fulfillment + Product Analysis domains; Bosch App Owner; international career (DE/NO/CH) |
+| 3 | Kubernetes, Cloud Native workloads, distributed systems | DIRECT | K8s at 2 employers (Swisscom + Bosch); AWS cloud-native data platform; Vizrt distributed video transcoding |
+| 4 | Data pipelines, storage & analysis (the core of the role) | DIRECT | Swisscom Data Mesh / data products, Kafka pipelines, Teradata at scale; Bosch fab data |
+| 5 | **Go** (desire to write efficient Go) | BRIDGE (LOW-MED) | Polyglot: Python + Java production; C++ systems at Vizrt. NO Go production yet — frame as "desire/aptitude", emphasize systems + perf mindset. Do NOT claim Go experience. |
+| 6 | Robust APIs / gRPC | BRIDGE (MED) | Built/served production APIs; LiteLLM API gateway at Swisscom; REST services. gRPC specifically NOT confirmed — bridge as "API design", do not claim gRPC. |
+| 7 | Strong SQL + query optimization for large datasets | DIRECT | Teradata + large-scale SQL pipelines at Swisscom; performance tuning on big analytics workloads |
+| 8 | Large distributed columnar databases for analytics | DIRECT (bridge to their stack) | Teradata (MPP/columnar analytics); AWS Redshift/Athena; data-warehouse modelling |
+| 9 | ClickHouse (plus) | BRIDGE (HIGH) | Columnar-analytics-DB experience directly transferable; frame "columnar analytics DBs (Teradata/Redshift; transferable to ClickHouse)" |
+| 10 | Observability domain (Cilium/Tetragon/Hubble) | BRIDGE (HIGH — strong) | Bosch observability stack: ELK + Grafana + Prometheus + Loki; on-call SLA at Swisscom. Real observability-platform operator. |
+
+**Net:** 6 DIRECT, 3 strong bridges, 1 genuine gap (Go). One of the cleanest fits on the board — the role IS data engineering for an analytics/observability platform, which is Dennis's exact lane.
+
+### ATS Keywords
+- **Core:** data engineer, data pipelines, data platform, analytics, storage, query optimization
+- **Cloud-native:** Kubernetes, cloud native, distributed systems, containerized workloads
+- **Data stores:** SQL, columnar database, ClickHouse, data warehouse, MPP, large-scale datasets
+- **APIs:** API design, gRPC, services
+- **Languages:** Go (aspirational), Python, Java
+- **Domain:** observability, monitoring, security posture, eBPF, Cilium, Tetragon, telemetry
+- **Soft:** remote teams, cross-functional collaboration, ownership
+
+### Gap Assessment
+- **Direct:** education, K8s/cloud-native/distributed, data pipelines/storage/analysis, SQL + optimization, columnar analytics DBs, cross-functional/remote collaboration
+- **Bridge:** ClickHouse (HIGH — columnar DB transfer), observability domain (HIGH — Bosch stack), APIs/gRPC (MED — API design without gRPC claim)
+- **Gap (do NOT claim):** Go production experience (frame as aptitude/desire only); gRPC specifically (say "API design", not "gRPC")
+
+## Company Context
+- **Mission:** Isovalent (Cilium/eBPF creators, now Cisco) builds cloud-native networking, security & observability on eBPF. The observability stack = Hubble (network observability for Cilium) + Tetragon (runtime security observability), with data pipelines/storage/analysis behind them.
+- **This role:** Build the data backbone behind that observability — ingest high-volume eBPF telemetry, store it in columnar analytics DBs (ClickHouse-class), and build analysis that assesses customer security posture and surfaces recommendations. Success = scalable pipelines + fast analytical queries over very large telemetry datasets.
+- **Culture:** Open-source-first (Cilium is CNCF graduated), deeply technical, remote-friendly distributed eng org, Zurich is a real eng hub (Thomas Graf / founding team CH-based).
+- **"Why them" angle:** Dennis operated observability stacks (Grafana/Prometheus/Loki/ELK) as a *user* in a 24/7 Bosch fab and built large-scale data pipelines/products at Swisscom — this role is building the platform side of exactly what he ran. Plus cloud-native (K8s) + columnar-analytics-DB depth. Authentic, not a stretch.
+
+## Framing Strategy
+- **Lead narrative:** Senior data engineer who builds large-scale, cloud-native data platforms — pipelines, columnar analytics stores, and the SQL/query-optimization layer — and who has operated production observability stacks firsthand.
+- **Reframing map:**
+  - Data Mesh / data products → "cloud-native data platform / analytics pipelines"
+  - Teradata / Redshift → "large distributed columnar analytics databases (transferable to ClickHouse)"
+  - ELK/Grafana/Prometheus/Loki (operator) → "observability telemetry at scale"
+  - Kafka pipelines → "high-throughput data ingestion pipelines"
+  - SQL tuning → "query optimization over large datasets"
+- **Emphasize:** K8s/cloud-native, data pipelines + storage + analysis, SQL/query optimization, columnar analytics DBs, observability domain credibility, distributed systems
+- **Downplay:** GenAI/agentic content (off-thesis here), pure DevOps/IaC unless it supports the platform story, C++ overselling (per memory)
+- **CL hooks:** Cilium/Hubble/Tetragon observability data pipeline; running Grafana/Prometheus/Loki/ELK in a 24/7 fab; eBPF telemetry → columnar analytics; Cisco/Isovalent open-source ethos
+- **User directives:** No Go fabrication (gap). No gRPC claim (bridge as API design). Don't oversell C++ (memory). Honesty per anti-fabrication rules.
+
+## Critique Context
+- **Reviewer persona:** Isovalent/Cilium senior eng or eng manager — deeply technical, open-source-native, allergic to buzzword padding. Cares about real distributed-systems + data-at-scale chops, not titles. Will respect honest "I've run observability stacks, here's the data-platform work I've shipped."
+- **Competitive landscape:** Backend/data engineers from observability vendors (Datadog, Grafana Labs, Elastic) and cloud-native shops with Go + ClickHouse on their CV. Dennis's edge: operated the observability tools in a high-stakes 24/7 setting + broad data-platform ownership; his risk: no Go, no named ClickHouse.
+- **Domain vocabulary:** eBPF, Cilium, Hubble, Tetragon, CNCF, columnar OLAP, ClickHouse, cardinality, telemetry ingestion, Kubernetes operators, gRPC.
+
+## Cover Letter Plan
+- **Institution type:** Industry (open-source-rooted, cloud-native)
+- **Paragraph count:** 3–4 paragraphs, 250–300 words (1 page)
+- **P1 hook:** Reference Cilium/eBPF observability (Hubble/Tetragon) + the data-pipeline-behind-the-telemetry framing; connect to having operated Grafana/Prometheus/Loki/ELK in production.
+- **P2–P3 evidence:** Swisscom large-scale data pipelines/products + SQL/query optimization on big analytics workloads; K8s/cloud-native; columnar analytics DB depth (transferable to ClickHouse).
+- **Domain pivot:** "Operated observability at scale; eager to build the data platform that powers it" + honest Go-aptitude note (systems/perf mindset).
+- **Jargon level:** Technical (insiders read it)
+- **"Why them" hook:** Cisco/Isovalent open-source ethos + CH eng hub + the exact platform/data overlap.
+
+## Bullet Plan (Phase 1 — CONFIRMED 2026-06-02; generate 17: SW-2/1/7/3/6/4, BS-4/2/1/3, FC-3/1/2, VZ-1/2, GN-1/3)
+
+Position title themes (FLIPPED format — bold theme + role subtitle):
+- Swisscom: **Cloud-Native Data Platform, Pipelines & Observability at Telecom Scale**
+- Bosch: **Observability, Production ML & Data Services in 24/7 Semiconductor Manufacturing**
+- Fraunhofer: **Microservice Engineering & Applied Data Research**
+- Vizrt: **Distributed Real-Time Backend Engineering at Broadcast Scale**
+- Generali: **Test Automation, CI/CD & Java Backend**
+
+### Swisscom (5 bullets) — Staff Data, Analytics & AI Engineer, Oct 2023–Present
+| * | ID | Achievement | Variant | JD Match |
+|---|----|-------------|---------|----------|
+| * | SW-2 | Component Owner — Fulfillment+Product Analysis ETL (Oracle/Kafka→Teradata, Python); governance, on-call SLA | 2L | Direct (pipelines/storage) |
+| * | SW-1 | AWS migration (S3, Glue, Athena/Iceberg, **Redshift columnar**, Airflow, CloudFormation) | 2L | Direct (cloud-native + columnar DB) |
+| * | SW-7 | Data Mesh, data products & metadata management on AWS — governed, discoverable data platform | 2L | Direct (data platform/storage+analysis) |
+| * | SW-3 | Python data services on **Kubernetes** + GitLab CI/CD, containerized delivery | 2L | Direct (K8s/cloud-native) |
+| * | SW-6 | PySpark distributed processing over large datasets in the Data Lake | 2L | Direct (distributed/large-data + SQL) |
+| x | SW-GenAI | custom GPTs / LiteLLM agent assistants | -- | OFF-THESIS here — omit |
+| o | SW-4 | B2B data products + process automation | 2L | Available (page-fill option) |
+
+### Bosch (4 bullets) — (Senior) Data Engineer, Feb 2020–Dec 2022
+| * | ID | Achievement | Variant | JD Match |
+|---|----|-------------|---------|----------|
+| * | BS-4 | **Observability stack**: ELK + Kafka + Grafana/Prometheus/Loki, centralized monitoring/telemetry for 24/7 production | 2L | **Bridge HIGH (observability domain — key hook)** |
+| * | BS-2 | Data services over OracleDB + Hadoop/ImpalaSQL; **query optimization** for large analytics datasets | 2L | Direct (SQL/query-opt + columnar-ish) |
+| * | BS-1 | Containerized ML inference (Docker/K8s/Ansible) into 24/7 fab | 2L | Direct (K8s/distributed infra) |
+| * | BS-3 | Application Owner — SLOs, vendor mgmt, cross-functional adoption | 2L | Direct (ownership + cross-functional) |
+
+### Fraunhofer (2–3 bullets) — Research Software Engineer, Sep 2018–Oct 2019
+| * | ID | Achievement | Variant | JD Match |
+|---|----|-------------|---------|----------|
+| * | FC-3 | Microservices (Express.js, Docker, **REST APIs**, SQLite) for MISSION data-exchange platform | 2L | Bridge MED (API design — gRPC proxy) |
+| * | FC-1 | Independently set up Jenkins CI/CD with quality gates; SCEDAS DSS (C#/.NET/SQL) | 2L | Bridge (CI/CD initiative) |
+| o | FC-2 | ARTUS ML/NLP sea-rescue transcription (hedged: "Contributed") | 2L | Available (ML breadth; off core thesis) |
+
+### Vizrt (2 bullets) — DevOps Engineer, Jul 2017–May 2018
+| * | ID | Achievement | Variant | JD Match |
+|---|----|-------------|---------|----------|
+| * | VZ-1 | **Distributed real-time** video transcoding backend (Python, legacy C++); CNN/BBC/Al Jazeera | 2L | Direct (distributed systems) |
+| * | VZ-2 | Automated A/V test suite (Python) + CI/CD quality gates | 2L | Bridge (CI/CD) |
+
+### Generali (2 bullets) — IT Consultant, May 2015–Jun 2017 (Hamburg — KB corrected)
+| * | ID | Achievement | Variant | JD Match |
+|---|----|-------------|---------|----------|
+| * | GN-1 | Introduced BDD test automation; technical ownership + team training | 2L | Weak (initiative signal) |
+| o | GN-3 | Java/J2EE features; XLDeploy; Apache Camel/Spring Boot PoC | 2L | Available (page-fill) |
+
+**Recommended set:** 5 + 4 + 2 + 2 + 1 = **14 core**, expandable to 17 with `o` options (SW-4, FC-2, GN-3) for page fill.
+**Go handling:** NOT in any bullet (no fabrication). Go aptitude lives in Summary tagline + Skills only ("polyglot; Python/Java/C++; learning Go").
+**Security Champion (SW-5):** omitted — JD's "security posture" is about the product, not the engineer; and per KB it's 2025/26 team role only, not an award.
+
+## Output Files
+- Resume: `output/Isovalent_DataEngineer/e2e_isovalent_data_engineer_resume.tex`
+- Cover Letter: `output/Isovalent_DataEngineer/e2e_isovalent_data_engineer_cover_letter.tex`
+- Critique: `output/Isovalent_DataEngineer/critique_isovalent_data_engineer.md`
+
+## Status
+- Phase 0: DONE
+- Phase 1: DONE (19 bullets confirmed: SW-2/1/7/3/6/4/5, BS-4/2/1/3, FC-3/1/2, VZ-1/2, GN-1/2/3)
+- Phase 2 Resume:
+  - Summary: DONE
+  - Skills: DONE (5 groups 4-3-2-2-2, retuned for data-eng/observability/columnar; crypto+agentic dropped)
+  - All positions: DONE
+  - Compile: DONE (2 pages; page 2 ~70% full — strong set, not padded)
+- Cover Letter: DONE (1 page, ~302 words, industry 4-para; compiled clean via MiKTeX)
+- Critique: CURRENT — **84.5/100** (2026-06-02); **Tier 1 fixes applied 2026-06-02 → est. ~86/100**
+  - ✓ Bullet 3 reframed: "Built governed data products ... within Swisscom's company-wide Data Mesh" (no longer claims building the Mesh)
+  - ✓ Summary scoped: "I build and own cloud-native data pipelines and products on ... telco's AWS platform"
+  - ⚠ Still verify "currently learning Go" is literally true before sending
+  - Recompiled clean (2pp), char counts OK (bullet 3 = 204)
+- **FINALIZED 2026-06-02** — submission PDFs: `Dennis_Thiessen_Resume.pdf`, `Dennis_Thiessen_Cover_Letter.pdf` (~86/100). Reminder before sending: confirm "currently learning Go" is literally true.
+- **🔴 ROLE PULLED — CONFIRMED CLOSED (2026-06-02):** Verified via live headless-browser scrape (job_scout `.venv` Playwright, `keywords=Isovalent` on careers.cisco.com). 10 live Isovalent/Cilium CH roles returned; **"Senior Data Engineer, Observability" is NOT among them.** Original Recruitee apply link also dead (→ `recruitee.com/careers_not_hosted`). Two independent signals = role closed/pulled.
+- **Remaining live Isovalent roles are off-lane:** Tetragon kernel/Linux-security eng + EMs, eBPF Agent/Datapath SWE, "Senior SWE Go — WAF" (Go-first), Dev-Experience SWE. All are low-level systems/Go/management — opposite Dennis's data-platform lane (per [[user_positioning]]). None worth retargeting this package to.
+- **DISPOSITION: SHELVED.** Finalized PDFs (`Dennis_Thiessen_Resume.pdf` / `_Cover_Letter.pdf`, ~86/100) kept as a reusable data-eng/observability package for the next live req. Natural next targets from scout: QuantCo, Grafana Labs, Confluent.
+
+## Critique Summary (2026-06-02 — score 84.5/100)
+- **Verdict:** Strong, submit-ready after 2 accuracy tightenings. One of the cleanest fits on the board (role IS data-eng for an observability/analytics platform). ATS ~85%, HM = INTERVIEW, ceiling ~88–89 (capped by no production Go / no named ClickHouse).
+- **Tier 1 (accuracy — do these):**
+  1. Bullet 3 "Built a decentralized Data Mesh" overclaims sole ownership of a company-wide platform → reframe to own the data products/modelling/onboarding *within* Swisscom's company-wide Data Mesh (per KB Data-Mesh ownership rule). +1.0
+  2. Summary "I own ... the cloud-native data platform" too broad → scope to pipelines/products/domains (CL is already better-scoped; align summary to it). +0.5
+  3. Verify "currently learning Go" is literally true before sending (blocking gate, not score).
+- **Tier 2 (optional):** Bosch position-title header wraps the date to a 2nd line — shorten title (+0.3); reconsider Security Champion bullet SW-7 (weakest, but mildly on-thesis since JD = "security posture" — defensible to keep); "high-volume batch" → "high-throughput ingestion" vocab swap.
+- **Tier 3 (skip):** vary ~8 trailing -ing participial-clause bullet endings; "AWS Solutions Architect" → "AWS Certified Solutions Architect".
+- **AI fingerprint:** PASS (0 em-dashes, no banned words/phrases). **Compile:** both clean via MiKTeX, resume 2pp / CL 1pp.
+- **Accuracy verified clean:** Generali=Hamburg, Bosch=Dresden, edu dates KB-correct, German/English only, no gRPC/Go fabrication, C++ downplayed, no LangChain.
+
+## CL Hook Verification (2026-06-02 — all VERIFIED)
+- Cilium = eBPF data plane, **CNCF-graduated** (Oct 2023) → confirmed
+- Hubble = Cilium network observability; Tetragon = runtime/network security observability built on Cilium/Hubble → confirmed
+- Isovalent acquired by **Cisco** (announced Dec 2023, closed 2024) → confirmed
+- Founding team (CTO Thomas Graf) **Zurich-based**; Isovalent HQ Cupertino + Zurich → confirmed CH eng hub
+- Sources: cisco blogs, sdxcentral, isovalent.com/about-us, theregister
+
+## Generation notes / accuracy flags
+- **"currently learning Go"** in summary + "Go (learning)" in skills: per user's confirmed honest-polyglot framing. VERIFY this is actually true before submitting (or start a Go tutorial first).
+- Go appears in NO bullet (no fabrication). gRPC NOT claimed (skills say "REST APIs ... OpenAPI" only).
+- "ClickHouse-class columnar analytics (transferable from Teradata/Redshift/Impala)" — framed as transferable, not claimed experience.
+- Education dates corrected to KB-verified (B.Eng Oct 2009–Oct 2012, M.Eng Apr 2012–Oct 2013). NOTE: the sent Kraken resume has WRONG dates (2007–2010 / 2010–2013).
+- Generali location = Hamburg (KB-corrected). Security Champion = 2025/26 team role, not award.