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feat: rebuild evidence-first application workflow

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dennisthiessen
2026-07-27 17:56:15 +02:00
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resume_builder/bundles/bundle_analytics_engineer.md
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|----|----------------|--------------------|--------------------|
| SW-4 | B2B products + automation | **Lead bullet** — "Delivered data products, analyses and dashboards for B2B stakeholders; drove automation of recurring technical workflows" | Stakeholder-facing delivery |
| SW-2 | Component Owner ETL | "Owned Fulfillment ETL pipelines (Oracle/Kafka → Teradata) — ensuring data availability for downstream analytics with SLA accountability" | Pipeline → analytics link |
| SW-1 | AWS migration | "Migrated ETL stack to AWS (S3, Glue, Athena/Iceberg, Redshift, Airflow) — enabling scalable, query-optimized analytics on a cloud data lakehouse" | Iceberg/Athena = analytics stack |
| SW-1 | AWS migration | "Migrated pipelines in his owned domains onto Swisscom's AWS platform (S3, Glue, Athena/Iceberg, Redshift, Airflow)" | Scoped delivery on a current analytics stack; no unverified scale claim |
| BS-3 | Application Owner | "Application Owner for semiconductor data analysis platforms — defined SLOs, trained users, managed vendor relationships and stakeholder expectations" | Ownership + analytics platform |
| BS-2 (generic) | Data services | "Built data services supplying analysis teams with on-demand structured access to manufacturing process data" | Analytics enablement framing |
| BS-2 (semi JD) | Data services | "Built data services enabling Defect Management, Parameter Testing and Process Analysis teams with on-demand data access" | Semiconductor domain specificity |
@@ -109,12 +109,12 @@ Python, SQL (Oracle · Teradata · Athena), AWS (S3 · Glue · Athena · Redshif
**Key narrative thread:**
1. **Analytics platform ownership** — App Owner at Bosch: not just building queries, but owning the analytics software that teams depend on
2. **Pipeline-to-insight chain** — Fulfillment Component Owner at Swisscom: show the full chain from raw Oracle/Kafka data → Teradata DWH → B2B analytics
3. **Cloud analytics stack** — AWS migration with Athena/Iceberg/Glue: modern lakehouse architecture for analytics workloads
3. **Cloud analytics stack** — hands-on migration of owned-domain pipelines using Athena/Iceberg/Glue within a wider programme
4. **Semiconductor domain** (for semi JDs): Defect Management + Parameter Testing + Process Analysis — rare domain expertise in an Analytics Engineer candidate
**"Why them" angle to research:**
- What business domain are their analytics teams serving? Map to Swisscom (telecom) or Bosch (manufacturing) experience
- What is their analytics stack? AWS-heavy → your SW-1 migration is directly relevant
- What is their analytics stack? AWS-heavy roles can use SW-1 directly when company-wide ownership is not implied
- Do they use dbt? Flag if so — not in your stack, but Airflow/Glue is adjacent
**Avoid:**
resume_builder/bundles/bundle_data_engineer.md
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| ID | Default Framing | This Role's Framing | Key Metric / Signal |
|----|----------------|--------------------|--------------------|
| 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 |
| SW-1 | AWS migration | "Migrated legacy Teradata/Oracle ETL stack to AWS (S3, Glue, Athena/Iceberg, Redshift, Airflow, CloudFormation)" | Cloud-native stack breadth; Iceberg signals modern data lakehouse |
| 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 |
| 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 |
| BS-3 | Application Owner | "Application Owner for semiconductor analytics suite — SLOs, vendor management, training, documentation" | SLO ownership = senior signal |
| 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 |
@@ -106,7 +106,7 @@ Python, Kafka, AWS (S3 · Glue · Athena · Redshift · Airflow · CloudFormatio
**Key narrative thread:**
1. **Ownership at scale** — Component Owner at Swisscom, Application Owner at Bosch: not just building pipelines, but running them in production with SLA accountability
2. **Cloud-native evolution** — AWS migration (Athena/Iceberg, Glue, Airflow, CloudFormation): led the transition, not just participated
2. **Cloud-native evolution** — primary engineer for his domains' migration work and contributor to the wider programme; never imply company-wide leadership
3. **Production ML integration** — Bosch: ML inference containerized into 24/7 fab; demonstrates that "data engineer who can own the ML data layer"
4. **Consistent seniority arc** — Bosch promotion (mid → Senior), Swisscom promotion (Senior → Staff)
resume_builder/bundles/bundle_data_platform.md
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## S1: Role Profile & Priority Matrix
**Positioning:** Dennis's data platform and infrastructure experience is woven throughout his career rather than being a dedicated "platform engineer" role — but the evidence is substantive: Kubernetes ownership at two employers, AWS migration with CloudFormation/IaC, GitLab CI/CD automation, Docker containerization of ML workloads, observability stack (ELK + Grafana + Prometheus), and 3 consecutive years as Swisscom Security Champion (DevSecOps). Position as "Data Engineer with strong platform and infrastructure ownership" rather than a dedicated Platform/SRE/DevOps role.
**Positioning:** Dennis's platform evidence sits inside data-engineering roles rather than a dedicated Platform/SRE title: Kubernetes delivery at Swisscom and Bosch, scoped AWS migration work with CloudFormation, GitLab CI/CD, Dockerized ML inference and an observability proof of concept. Position as a data engineer with production-platform depth, not as a dedicated SRE, developer-platform or Terraform engineer.
**Note on Tier 3:** This bundle is viable but slightly less natural than Tier 1/2. The gap is: Dennis doesn't have a dedicated platform engineering title, and his infrastructure work is in service of data pipelines rather than standalone infrastructure. Frame accordingly — emphasize that his platform skills are production-proven, not academic.
@@ -39,7 +39,7 @@
- "Kubernetes-based containerized pipeline deployment"
- "AWS IaC (CloudFormation)" — infrastructure-as-code signal
- "AWS migration" — hands-on cloud platform experience
- "DevSecOps / Security Champion" — security-aware platform engineer
- Security Champion is not a default positioning theme; use the 2025/2026 team role only when the JD explicitly requires security exposure
- "ELK + Grafana + Prometheus observability stack"
**Tone:** Infrastructure-minded engineer who thinks about reliability, observability, and security — not just data throughput. Platform thinking embedded in data work.
@@ -56,11 +56,11 @@
| ID | Default Framing | This Role's Framing | Key Metric / Signal |
|----|----------------|--------------------|--------------------|
| SW-3 | K8s + GitLab | **Lead bullet** — "Deployed and operated Python data applications on Kubernetes with GitLab CI/CD; drove infrastructure automation in agile DevOps team" | K8s + CI/CD ownership = core platform signal |
| SW-1 | AWS migration | "Migrated legacy ETL stack to cloud-native AWS (S3, Glue, Athena/Iceberg, Redshift, Airflow, CloudFormation) — full IaC stack provisioned via CloudFormation" | CloudFormation/IaC + full AWS service breadth |
| SW-1 | AWS migration | "Migrated pipelines in his owned domains from legacy Teradata/Oracle processing onto Swisscom's AWS platform (Glue, Athena/Iceberg, Redshift, Airflow, CloudFormation)" | Scoped migration delivery plus AWS breadth |
| SW-2 | Component Owner | "Owned Fulfillment ETL pipelines (Oracle/Kafka → Teradata) — platform reliability, Data Governance compliance, 2nd/3rd-level support and on-call duty" | Platform SLA + on-call = reliability engineer signal |
| BS-1 | ML inference | "Containerized and orchestrated ML inference (Docker, K8s, Ansible) into 24/7 semiconductor production — zero-downtime constrained deployment" | Production-grade containerization under hardest constraints |
| BS-4 | ELK PoC | "Designed and delivered observability stack: ELK + Kafka, Grafana dashboards, Prometheus metrics, Loki log aggregation — full monitoring suite for manufacturing infrastructure" | Full observability stack implementation |
| SW-5 | Security Champion | "Swisscom Security Champion ×3 (2023–2026) — DevSecOps ownership, security compliance, risk monitoring and deviation tracking for Data Lake team" | Security ownership in platform context |
| SW-5 | Security Champion | "2025/2026 team Security Champion; include only if the JD explicitly requires security or DevSecOps exposure" | Secondary team-role evidence, not ownership or certification |
| BS-2 | Data services | "Built multi-language data services (Python/Java/C#) over OracleDB and Hadoop/ImpalaSQL — platform-layer data access for semiconductor analysis teams" | Enterprise DB + Hadoop infrastructure |
| BS-3 | App Owner | "Application Owner for semiconductor analytics platform — SLOs, reliability, vendor management, on-call coverage" | Platform SLA ownership |
| FC-1 | CI/CD initiative | "Independently introduced Jenkins CI/CD pipeline with quality gates at Fraunhofer CML — first build automation adopted by the research team" | Initiative: built CI/CD from zero |
@@ -112,7 +112,7 @@ Kubernetes, Docker, AWS (S3 · Glue · Athena · Redshift · CloudFormation), Ka
1. **Production Kubernetes** — SW-3 + BS-1: K8s at two employers, in different contexts (data apps at Swisscom, ML inference at Bosch). Cross-employer K8s ownership is a strong signal.
2. **Full AWS platform stack** — SW-1: Not just using one AWS service — migrating an entire ETL infrastructure to AWS with CloudFormation/IaC shows platform-level thinking.
3. **Observability initiative** — BS-4: Self-initiated ELK + Prometheus + Grafana PoC shows platform engineer mindset (monitoring is not optional).
4. **Security ownership** — SW-5: Security Champion ×3 = DevSecOps embedded in platform work, not an afterthought.
4. **Operational accountability** — use Component/Application Owner evidence. Security Champion is optional and never a substitute for production ownership.
**"Why them" angle to research:**
- What is their cloud stack? If AWS-heavy → your SAA cert + migration experience is directly relevant
resume_builder/bundles/bundle_ml_ai_engineer.md
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| SW-2 | Component Owner | "Owned business-critical ETL pipelines (Oracle/Kafka → Teradata) — reliable data supply for downstream ML and analytics" | Data reliability for ML input |
| FC-2 | ARTUS NLP | "Contributed ML and speech recognition components to ARTUS — Fraunhofer research project targeting automatic sea rescue transcription" | Applied NLP in safety-critical domain |
| BS-4 | ELK PoC | "Delivered anomaly detection PoC: ELK + Kafka pipeline with Grafana/Prometheus monitoring — ML-adjacent signal processing" | Anomaly detection / observability |
| SW-5 | Security Champion | "Swisscom Security Champion ×3 — security and compliance ownership for ML pipeline data governance and DevSecOps" | Security in ML data pipeline context |
| SW-5 | Security Champion | Omit by default. If explicitly relevant: "2025/2026 team Security Champion" | Security exposure only; not responsible-AI, model-security or compliance ownership |
| BS-2 | Data services | "Built data services (Python/Java/C#) over OracleDB and Hadoop enabling ML model input pipelines in semiconductor manufacturing" | Data infrastructure for ML |
---
resume_builder/bundles/bundle_semiconductor.md
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# Bundle: Semiconductor Data / AI Engineer
## 1. Role Profile and Evidence Priority
**Positioning:** Production data and ML-integration engineer with three years of direct semiconductor-fab experience. Lead with Bosch domain evidence, then Swisscom production data ownership. Do not present Dennis as a process engineer, model researcher or computer-vision model owner.
**Good-fit roles:** Semiconductor data engineer, manufacturing analytics engineer, ML platform/MLOps engineer, data-infrastructure engineer, analytics-application owner.
**Hard-gate cautions:** Treat process-integration ownership, yield engineering, model research/training, embedded/edge inference, cleanroom equipment engineering and relocation requirements as direct gaps unless the JD makes them optional.
| Priority | Achievement | Why |
|---|---|---|
| HIGH | BS-1 ML inference integration | Direct production-ML evidence in a 24/7 fab |
| HIGH | BS-3 Application Owner | Operational accountability, vendors, SLOs, training |
| HIGH | BS-2 Data services | Python/Java/C# plus Oracle and Hadoop/Impala in fab domains |
| MED | BS-5 Spotfire co-ownership | Fab analytics, C# extensions, user enablement |
| MED | BS-4 Observability PoC | Honest proof-of-concept evidence for monitoring |
| MED | SW-2 Component Owner | Current production ownership and on-call responsibility |
| MED | SW-1 Scoped AWS migration | Current cloud/data-platform evidence |
| LOW | Older software roles | Use only to support a required language or delivery practice |
## 2. Summary Guide
Use at most 2--3 rendered lines. State the Bosch fab context, production ML integration and current Staff-level data ownership. Avoid generic claims about petabyte-scale fabs, yield impact or zero downtime unless directly verified.
## 3. Reframing Rules
| Source evidence | Safe semiconductor framing |
|---|---|
| BS-1 | Integrated containerized ML inference into a continuously operating 300mm fab environment |
| BS-2 | Built services giving internal analysis teams access to defect-management and process-analysis data |
| BS-3 | Owned analytics applications and upstream pipelines operationally |
| BS-4 | Built an anomaly-detection and monitoring proof of concept; never call it the fab observability platform |
| BS-5 | Co-owned Spotfire and built wafer-map visualizations; preserve co-ownership |
| SW-2/SW-1 | Current production data ownership and AWS migration work; do not force semiconductor vocabulary onto Swisscom |
## 4. Skills Guide
Prefer: Python, SQL, Oracle, Hadoop/Impala, Docker, Kubernetes, Ansible, Kafka, ELK, Grafana, Prometheus, C#, Java, Spotfire. Include only skills allowed by `resume_builder/canonical/claims.json`.
## 5. Cover Letter Guide
Generate a letter only when requested or when the Bosch-to-target-company domain connection adds information not obvious from the resume. Use first-person evidence from Bosch. Company/fab scale belongs to context, never to Dennis's personal achievement. Do not use the generic petabyte or yield-value claims from significance research.