dennisthiessenandClaude Opus 5
f515a1e522
D1/D2 - Bosch title and promotion: CONFIRMED by the user. The promotion and its
timing are correct and came from a re-grading (Neueinstufung). The Zeugnis does
not contradict it - it names DEPARTMENTS ("Ingenieur" in Fertigungstechnologie
1/2/3) rather than job titles. Separately corrected a false provenance note that
claimed official_title was "the formal combined string on the Zeugnis"; it never
came from that document, it comes from the user and LinkedIn.
D3 - part-time from 2021-09: NOT recorded, by the user's decision. Noted for
completeness that tenure wording such as "over ten years" measures elapsed time
and is unaffected; it would only matter if a document claimed FTE years, and
none does.
D4 - French and Italian: the Swisscom Zwischenzeugnis says he uses both
professionally on a regular basis. The user reviewed the sentence and confirmed
it is an ERROR IN THE DOCUMENT. DE/EN only stands. Recorded in
identity.language_note so nobody rediscovers the line and acts on it, with the
practical warning that a reader of that Zeugnis may take it at face value.
D5 - the RUAG MSSQL rule-out: the DECISION stands (user does not want it
revisited), the REASONING is corrected. Two of its four premises were wrong:
MSSQL is not 0 (Fraunhofer SCEDAS ran on Microsoft SQL Server), and "his stack
is AWS cloud-native" was too narrow - the Swisscom Zeugnis documents component
ownership for ETL into the Teradata DWH. Talend and SAP S/4HANA remain genuinely
0, and the required line reads "Aufbau UND Betrieb" while he has documented
Betrieb only - so the skip is still defensible, it was just better than its
written justification. Both RUAG decision rows now carry the correction and a
standing rule for future DWH postings.
D6 - Vizrt end date: 2018-05 stands by the user's decision.
And the follow-through that matters: the data-warehouse, MSSQL and mentoring
evidence is now IN THE BUNDLES, not only in claims.json. BS-6 showed last week
that evidence which reaches no bundle cannot be selected - this is the same
failure mode, caught the same week. The DWH entry carries its scope limit
explicitly: documented Betrieb, not Aufbau.
Validator PASS, 37/37 tests.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qej5SBvhcbGXHwLqNWiskM
154 lines
9.6 KiB
Markdown
154 lines
9.6 KiB
Markdown
# Bundle: Staff / Senior Data Engineer
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> Target employers: Tech companies, scale-ups, platform teams
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> Tier: 1 — strongest evidence, full portfolio
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> Config key: bundle_data_engineer.md
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---
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## S1: Role Profile & Priority Matrix
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**Positioning:** Dennis is a Staff-level data engineer with 5+ years building production-grade ETL pipelines and data platforms at scale — from Oracle/Teradata DWH ownership at Swisscom (Switzerland's largest telco) to containerized ML inference in a 24/7 semiconductor fab at Bosch. His AWS certification (SAA, active), cloud migration ownership, and Kubernetes-based deployment experience position him as a senior-to-staff candidate across data engineering, data platform, and data infrastructure roles.
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**Promotion signal to use:** "Promoted from Senior to Staff Engineer (Engineer IV) at Swisscom, April 2025."
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### Priority Matrix
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| Priority | Achievement IDs | Rationale |
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|----------|----------------|-----------|
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| HIGH | SW-2, SW-1, SW-3, BS-3, BS-1, BS-2 | Core DE ownership: component owner, AWS migration, K8s/CI/CD, app owner, ML pipelines, data services |
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| MED | SW-4, SW-5, SW-6, BS-4, FC-1, VZ-2, GN-1 | Breadth signals: stakeholder products, DevSecOps, PySpark, ELK PoC, CI/CD, BDD ownership |
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| LOW | FC-2, FC-3, VZ-1, GN-2, GN-3, CA-1 | Earlier career / non-core for this audience |
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**2-page resume bullet allocation (typical):**
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- Swisscom: 3–4 bullets (SW-1, SW-2, SW-3, SW-4 or SW-5)
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- Bosch: 3 bullets (BS-1, BS-2, BS-3; +BS-4 if space)
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- Fraunhofer: 1–2 bullets (FC-1 compressed)
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- Vizrt: 1 bullet (VZ-1 + VZ-2 combined)
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- Generali: 1 bullet (GN-1)
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---
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## S2: Summary Guide
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**Headline pattern:**
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> "Staff Data Engineer | AWS · Kafka · Kubernetes | ETL Pipelines, Cloud Migration & Production ML"
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**Building blocks** (3–5 phrases that should appear in summaries for this role type):
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- "end-to-end ETL pipeline ownership" or "component ownership of business-critical data pipelines"
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- "cloud migration" or "legacy-to-AWS migration"
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- "Kafka-based event-driven ingestion"
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- "Kubernetes deployment" or "containerized data applications"
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- "AWS Certified Solutions Architect" (cert signal)
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**Tone:** Engineer who owns systems, not just builds them. Accountability + delivery. Operator mindset.
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**Avoid:**
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- Academic or research framing
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- "Passionate about data" clichés
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- Overemphasizing testing/QA background (earlier career)
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- Listing every tool — focus on the stack that matters for the JD
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---
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## S3: Achievement Reframing Map
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| ID | Default Framing | This Role's Framing | Key Metric / Signal |
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|----|----------------|--------------------|--------------------|
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| SW-2 | Component Owner, Fulfillment ETL | **Lead bullet** — "owned business-critical Fulfillment pipelines end-to-end, on-call SLA, Data Governance compliance" | Component Owner title, on-call accountability |
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| SW-1 | AWS migration | "Migrated his domains' Teradata/Oracle pipelines onto Swisscom's AWS platform (S3, Glue, Athena/Iceberg, Redshift, Airflow, CloudFormation)" | Scoped migration delivery; Iceberg shows current lakehouse practice |
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| SW-3 | K8s + GitLab CI/CD | "Deployed and operated Python data apps on Kubernetes with GitLab CI/CD in agile DevOps team" | K8s + CI/CD = full DevOps ownership |
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| BS-3 | Application Owner | "Application Owner for semiconductor analytics suite — SLOs, vendor management, training, documentation" | SLO ownership = senior signal |
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| BS-1 | ML inference in fab | "Containerized ML inference (Docker, K8s, Ansible) into 24/7 production; automated image-based defect classification" | Production ML in constrained environment |
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| BS-2 | Data services Oracle/Hadoop | "Built Python/Java/C# data services over OracleDB and Hadoop/ImpalaSQL for semiconductor analysis teams" | Multi-language, enterprise DB breadth |
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| SW-4 | B2B products | "Delivered data products and dashboards for B2B stakeholders; drove process automation" | Stakeholder-facing breadth |
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| BS-4 | ELK PoC | "Delivered anomaly detection PoC: ELK + Kafka, Grafana/Prometheus/Loki monitoring" | Observability initiative |
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---
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## S4: Skills Guide
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**Bold tools (resume Technical Skills section):**
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Python, Kafka, AWS (S3 · Glue · Athena · Redshift · Airflow · CloudFormation), Kubernetes, Teradata
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**Must-include skills (ATS match):**
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- Python, SQL, ETL/ELT
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- Apache Kafka, Apache Airflow
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- AWS (S3, Glue, Athena, Redshift), Apache Iceberg
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- Kubernetes, Docker, GitLab CI/CD
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- Teradata, Oracle DB
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- PySpark
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**Nice-to-have (include if JD mentions):**
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- SAP BODS, Hadoop/Impala, Step Functions, Lambda
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- Grafana, Prometheus, ELK Stack
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- Ansible, IaC/CloudFormation
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- dbt (not evidenced — do NOT claim if not in JD; omit)
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**Omit:**
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- RPA/UIPath, Camunda, IBM ODM (too early-career/non-core)
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- HP Quality Center, Serenity-BDD, JBehave (testing tools — irrelevant)
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- C++, J2EE (legacy — omit unless JD explicitly asks)
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**Certifications to highlight:**
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- AWS Certified Solutions Architect – Associate (active, 2024–2027) → HIGH value for this role type
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- Data Engineering with AWS (Udacity, 2026) → supporting signal
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- iSAQB CPSA Foundation Level → supporting (architecture awareness)
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---
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## S5: Cover Letter Guide
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**Institution type:** Industry — tech company, scale-up, or enterprise platform team
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**Opening hook pattern:**
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> "As a Staff Data Engineer at Swisscom — Switzerland's largest telco — I currently own the business-critical Fulfillment ETL pipelines that feed our data warehouse, and I migrated my own domains' pipelines onto the company's AWS platform as part of its wider cloud migration programme. [Tie to their specific need / JD signal]."
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> **Scope warning (corrected 2026-08-21).** This hook previously read "*leading the migration of our legacy stack*", which contradicts both `claims.json` SW-1 (`forbidden`: "led the migration of the legacy warehouse", "sole technical lead") and point 2 of the narrative thread directly below. Never pair a full-ownership verb with a company-scale object. See CLAUDE.md → Scope Discipline.
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**Key narrative thread:**
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1. **Ownership at scale** — Component Owner at Swisscom, Application Owner at Bosch: not just building pipelines, but running them in production with SLA accountability
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2. **Cloud-native evolution** — primary engineer for his domains' migration work and contributor to the wider programme; never imply company-wide leadership
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3. **Production ML integration** — Bosch: ML inference containerized into 24/7 fab; demonstrates that "data engineer who can own the ML data layer"
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4. **Consistent seniority arc** — Bosch promotion (mid → Senior), Swisscom promotion (Senior → Staff)
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**"Why them" angle to research:**
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- What is their data stack? Match Kafka/Airflow/AWS overlaps explicitly
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- Are they migrating to cloud or lakehouse architecture? → Your SW-1 experience is directly relevant
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- Do they operate pipelines in production SLAs? → Component Owner + on-call duty is your signal
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**Avoid:**
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- Starting with "I am passionate about data"
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- Listing all tools in paragraph form
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- Mentioning Bundeswehr unless specifically relevant (leadership angle for management-adjacent roles)
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- Overplaying test automation background
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## Infrastructure and Linux operations (BS-6) — added 2026-09-11, review F07
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BS-6 was absent from every bundle although it has been canonical since 2026-08-27, so genuine strengths never reached the selection paths.
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- **Linux administration and automation at Bosch (2020–2022):** Linux servers carried the ML platform, Docker hosts, backend services and the Ansible control path.
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- **Ansible beyond a single project:** configuration management and infrastructure automation, including self-written extensions (a credential plugin with local caching).
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- **Use it when** the JD names Linux, Ansible, configuration management, IaC or platform operations — exactly the DevOps/SRE-flavoured reqs where this profile reads thin without it.
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- **Currency limit, always state it:** employer-side Linux/Ansible ended Dec 2022; `PP-3` carries the current half and is a **personal** self-hosted Debian server. Never present PP-3 as employer work or as physical-datacenter evidence.
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- **GitOps remains forbidden:** playbooks lived in Git but ran push-based from Jenkins/GitLab with no reconciliation agent. The substance is writable as “version-controlled infrastructure automation with Ansible from Git, executed through Jenkins/GitLab pipelines”.
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## Data-warehouse and mentoring evidence (added 2026-09-11 from the Arbeitszeugnisse)
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Both were documented all along and reached no bundle, so the selection paths could not see them.
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Same failure mode as BS-6 (Linux/Ansible), found the same week.
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- **Data warehouse (SW-2).** The Swisscom Zwischenzeugnis documents *Komponentenverantwortung* for
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the ETL pipelines that load business-critical Fulfillment data from Oracle into the **Teradata
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Data Warehouse (DWH)**. Use this whenever a JD names data warehousing — it was previously
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screened as absent, which cost a correct answer on at least one posting.
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**Scope limit:** this is documented **Betrieb** (operation) of a DWH, not **Aufbau**
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(construction). A required line saying *"Aufbau und Betrieb von Data-Warehouse-Lösungen"* is only
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half met — say which half.
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- **Microsoft SQL Server (FC-1).** Fraunhofer's SCEDAS ran on MSSQL with C# and Entity Framework.
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Historical and single-project; do not present it as data-platform depth.
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- **Mentoring (BS-7).** *"Fachliche Betreuung von Studierenden, auch im Rahmen von
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Abschlussarbeiten"* — documented technical supervision, including thesis supervision. Use it when
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a JD asks about developing other engineers (SBB asked explicitly and the answer had to fall back
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on team roles). **Technical supervision, NOT people management.**
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