# Bundle: Data Platform / Infra

> Target employers: Cloud-first companies, AWS-heavy orgs
> Tier: 3 — viable with careful framing
> Config key: bundle_data_platform.md

---

## S1: Role Profile & Priority Matrix

**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.

### Priority Matrix

| Priority | Achievement IDs | Rationale |
|----------|----------------|-----------|
| HIGH | SW-3, SW-1, SW-2, BS-1, BS-2, BS-3, BS-4, SW-5 | K8s/GitLab, AWS/IaC, pipeline ownership, ML containerization, data services, ELK observability, DevSecOps |
| MED | SW-4, SW-6, FC-1, FC-3, VZ-2, BS-5 | Automation, PySpark, CI/CD initiative, microservices, quality gates |
| LOW | FC-2, VZ-1, GN-1, GN-2, CA-1 | Non-platform signals |

**2-page resume bullet allocation (typical):**
- Swisscom: 3–4 bullets (SW-3, SW-1, SW-2, SW-5)
- Bosch: 3 bullets (BS-1, BS-2 or BS-3, BS-4)
- Fraunhofer: 1 bullet (FC-1 — CI/CD initiative)
- Vizrt: 1 bullet (VZ-2 — quality gates in CI/CD)
- Generali: 1 bullet (GN-1 or omit)

---

## S2: Summary Guide

**Headline pattern:**
> "Data Platform Engineer | Kubernetes · AWS · Kafka | Cloud-Native Data Infrastructure, IaC & DevSecOps"

**Building blocks:**
- "cloud-native data infrastructure" or "data platform ownership"
- "Kubernetes-based containerized pipeline deployment"
- "AWS IaC (CloudFormation)" — infrastructure-as-code signal
- "AWS migration" — hands-on cloud platform experience
- 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.

**Avoid:**
- Leading with analytics or BI framing
- Overemphasizing test automation background
- Positioning as SRE or pure DevOps (the role was data engineering with platform ownership)

---

## S3: Achievement Reframing Map

| 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 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 | "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 |

---

## S4: Skills Guide

**Bold tools (resume Technical Skills section):**
Kubernetes, Docker, AWS (S3 · Glue · Athena · Redshift · CloudFormation), Kafka, GitLab CI/CD

**Must-include skills (ATS match):**
- Kubernetes, Docker, Ansible
- AWS (S3, Glue, Athena, Redshift, CloudFormation, Airflow), Apache Iceberg
- GitLab CI/CD, Jenkins
- Kafka, Apache Airflow
- Python, SQL
- ELK Stack, Grafana, Prometheus
- IaC / CloudFormation
- DevSecOps

**Nice-to-have (include if JD mentions):**
- Terraform (not evidenced — do NOT claim; flag if JD requires)
- Loki (log aggregation — from Bosch PoC)
- PySpark (distributed processing on platform)
- Ansible (Bosch ML orchestration)
- Oracle DB, Teradata (enterprise data platform experience)

**Omit:**
- BDD, Selenium, HP Quality Center, UIPath (testing — irrelevant)
- Tibco Spotfire, SAP BODS (application tools — irrelevant)
- RPA/Camunda (process automation — irrelevant)

**Certifications to highlight:**
- AWS Certified Solutions Architect – Associate → HIGH (platform credibility, architecture knowledge)
- Data Engineering with AWS → supporting
- iSAQB CPSA Foundation Level → MED (software architecture — relevant for platform design decisions)

---

## S5: Cover Letter Guide

**Institution type:** Cloud-first tech company, scale-up with AWS-heavy stack, enterprise platform team, or data infrastructure consultancy

**Opening hook pattern:**
> "Across my career at Swisscom and Bosch, I've owned data infrastructure at two ends of the spectrum: migrating Swisscom's legacy ETL stack to a cloud-native AWS platform (CloudFormation, Glue, Athena with Iceberg, Airflow) while operating Kubernetes-deployed Python applications with GitLab CI/CD — and containerizing ML inference into a 24/7 semiconductor production line at Bosch using Docker, Kubernetes, and Ansible. In both cases, the infrastructure had to be production-grade with no tolerance for downtime. [Tie to their platform challenge]."

**Key narrative thread:**
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. **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
- Do they use Kubernetes in production? → Cross-employer K8s experience is the signal
- Are they building their data platform from scratch vs. maintaining existing? → Tailor SW-1 (migration) vs. BS-4 (observability initiative) accordingly
- Terraform vs. CloudFormation? → Note that your experience is CloudFormation; Terraform familiarity may need bridging

**Avoid:**
- Leading with analytics or BI outcomes (platform audience cares about reliability and infrastructure)
- Claiming SRE/pure DevOps title (you were a data engineer with platform ownership)
- Overstating Terraform/Helm experience (not confirmed — do not claim)
- Mentioning SCEDAS, maritime research, BDD, or RPA
