# Bundle: Staff / Senior Data Engineer > Target employers: Tech companies, scale-ups, platform teams > Tier: 1 — strongest evidence, full portfolio > Config key: bundle_data_engineer.md --- ## S1: Role Profile & Priority Matrix **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. **Promotion signal to use:** "Promoted from Senior to Staff Engineer (Engineer IV) at Swisscom, April 2025." ### Priority Matrix | Priority | Achievement IDs | Rationale | |----------|----------------|-----------| | 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 | | 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 | | LOW | FC-2, FC-3, VZ-1, GN-2, GN-3, CA-1 | Earlier career / non-core for this audience | **2-page resume bullet allocation (typical):** - Swisscom: 3–4 bullets (SW-1, SW-2, SW-3, SW-4 or SW-5) - Bosch: 3 bullets (BS-1, BS-2, BS-3; +BS-4 if space) - Fraunhofer: 1–2 bullets (FC-1 compressed) - Vizrt: 1 bullet (VZ-1 + VZ-2 combined) - Generali: 1 bullet (GN-1) --- ## S2: Summary Guide **Headline pattern:** > "Staff Data Engineer | AWS · Kafka · Kubernetes | ETL Pipelines, Cloud Migration & Production ML" **Building blocks** (3–5 phrases that should appear in summaries for this role type): - "end-to-end ETL pipeline ownership" or "component ownership of business-critical data pipelines" - "cloud migration" or "legacy-to-AWS migration" - "Kafka-based event-driven ingestion" - "Kubernetes deployment" or "containerized data applications" - "AWS Certified Solutions Architect" (cert signal) **Tone:** Engineer who owns systems, not just builds them. Accountability + delivery. Operator mindset. **Avoid:** - Academic or research framing - "Passionate about data" clichés - Overemphasizing testing/QA background (earlier career) - Listing every tool — focus on the stack that matters for the JD --- ## S3: Achievement Reframing Map | 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 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 | | 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 | | SW-4 | B2B products | "Delivered data products and dashboards for B2B stakeholders; drove process automation" | Stakeholder-facing breadth | | BS-4 | ELK PoC | "Delivered anomaly detection PoC: ELK + Kafka, Grafana/Prometheus/Loki monitoring" | Observability initiative | --- ## S4: Skills Guide **Bold tools (resume Technical Skills section):** Python, Kafka, AWS (S3 · Glue · Athena · Redshift · Airflow · CloudFormation), Kubernetes, Teradata **Must-include skills (ATS match):** - Python, SQL, ETL/ELT - Apache Kafka, Apache Airflow - AWS (S3, Glue, Athena, Redshift), Apache Iceberg - Kubernetes, Docker, GitLab CI/CD - Teradata, Oracle DB - PySpark **Nice-to-have (include if JD mentions):** - SAP BODS, Hadoop/Impala, Step Functions, Lambda - Grafana, Prometheus, ELK Stack - Ansible, IaC/CloudFormation - dbt (not evidenced — do NOT claim if not in JD; omit) **Omit:** - RPA/UIPath, Camunda, IBM ODM (too early-career/non-core) - HP Quality Center, Serenity-BDD, JBehave (testing tools — irrelevant) - C++, J2EE (legacy — omit unless JD explicitly asks) **Certifications to highlight:** - AWS Certified Solutions Architect – Associate (active, 2024–2027) → HIGH value for this role type - Data Engineering with AWS (Udacity, 2026) → supporting signal - iSAQB CPSA Foundation Level → supporting (architecture awareness) --- ## S5: Cover Letter Guide **Institution type:** Industry — tech company, scale-up, or enterprise platform team **Opening hook pattern:** > "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]." > **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. **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** — 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) **"Why them" angle to research:** - What is their data stack? Match Kafka/Airflow/AWS overlaps explicitly - Are they migrating to cloud or lakehouse architecture? → Your SW-1 experience is directly relevant - Do they operate pipelines in production SLAs? → Component Owner + on-call duty is your signal **Avoid:** - Starting with "I am passionate about data" - Listing all tools in paragraph form - Mentioning Bundeswehr unless specifically relevant (leadership angle for management-adjacent roles) - Overplaying test automation background ## Infrastructure and Linux operations (BS-6) — added 2026-09-11, review F07 BS-6 was absent from every bundle although it has been canonical since 2026-08-27, so genuine strengths never reached the selection paths. - **Linux administration and automation at Bosch (2020–2022):** Linux servers carried the ML platform, Docker hosts, backend services and the Ansible control path. - **Ansible beyond a single project:** configuration management and infrastructure automation, including self-written extensions (a credential plugin with local caching). - **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. - **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. - **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”. ## Data-warehouse and mentoring evidence (added 2026-09-11 from the Arbeitszeugnisse) Both were documented all along and reached no bundle, so the selection paths could not see them. Same failure mode as BS-6 (Linux/Ansible), found the same week. - **Data warehouse (SW-2).** The Swisscom Zwischenzeugnis documents *Komponentenverantwortung* for the ETL pipelines that load business-critical Fulfillment data from Oracle into the **Teradata Data Warehouse (DWH)**. Use this whenever a JD names data warehousing — it was previously screened as absent, which cost a correct answer on at least one posting. **Scope limit:** this is documented **Betrieb** (operation) of a DWH, not **Aufbau** (construction). A required line saying *"Aufbau und Betrieb von Data-Warehouse-Lösungen"* is only half met — say which half. - **Microsoft SQL Server (FC-1).** Fraunhofer's SCEDAS ran on MSSQL with C# and Entity Framework. Historical and single-project; do not present it as data-platform depth. - **Mentoring (BS-7).** *"Fachliche Betreuung von Studierenden, auch im Rahmen von Abschlussarbeiten"* — documented technical supervision, including thesis supervision. Use it when a JD asks about developing other engineers (SBB asked explicitly and the answer had to fall back on team roles). **Technical supervision, NOT people management.**