# Achievement Reframing Guide — Dennis Thiessen

> Generated: 2026-03-28
> Role types from config.md: Staff/Senior Data Engineer | Analytics Engineer | ML/AI Engineer | Data Platform/Infra

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## How to Use

Each achievement has a **Significance** line (why it matters to any reader) and a role-type table showing how to frame, which verb to lead with, and whether to include or omit for that audience. Use this guide when selecting and ordering bullets during resume generation.

**Priority tiers:**
- **HIGH** — Lead bullet or include in all variants of this position
- **MED** — Include if page budget allows; adjust framing per role type
- **LOW** — Omit from resume; include in full CV or CL only

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## SWISSCOM ACHIEVEMENTS

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### SW-1: AWS Migration of Legacy ETL Stack
**Significance:** Demonstrates hands-on migration delivery for pipelines in Dennis's owned domains and contribution to a wider enterprise programme. It is a strong AWS/data-engineering signal without implying ownership of the company-wide migration.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | HIGH | Migrated | Lead with scale + operational impact (reduced overhead) |
| Analytics Engineer | HIGH | Migrated | Lead with "enabling analytics outcomes" — tie to downstream stakeholder value |
| ML/AI Engineer | MED | Migrated | Frame as "building the data infrastructure enabling ML workflows" |
| Data Platform/Infra | HIGH | Migrated / implemented | Lead with verified AWS services and the owned-domain scope; do not claim company-wide architecture ownership |

**Overclaiming warning:** No specific throughput/volume numbers available — do not invent. Use qualitative impact (operational overhead reduction, scalability improvement).

---

### SW-2: Component Ownership — Fulfillment ETL Pipelines
**Significance:** Component Owner is a staff-level accountability signal — owning reliability, compliance, and on-call for business-critical data. Demonstrates senior engineer maturity beyond pure development.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | HIGH | Owned | Lead with accountability: Component Owner, SLA, on-call. This is the flagship bullet. |
| Analytics Engineer | HIGH | Owned | Frame as "ensuring data availability for downstream analytics" — business impact angle |
| ML/AI Engineer | MED | Owned | Frame as "reliable data feed for ML model inputs" |
| Data Platform/Infra | HIGH | Owned | Lead with Kafka/Teradata infrastructure; de-emphasize "Fulfillment domain" context |

**Overclaiming warning:** None — employer-confirmed via Zeugnis.

---

### SW-3: Python Applications on Kubernetes + GitLab CI/CD
**Significance:** Kubernetes ownership at Staff level in a production environment — paired with GitLab CI/CD — is a strong infrastructure signal. Confirms the "SWE + Ops" hybrid identity from LinkedIn summary.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | HIGH | Deployed | Show DevOps ownership as part of the data engineering role |
| Analytics Engineer | MED | Deployed | Include only if JD mentions platform ownership; otherwise de-emphasize |
| ML/AI Engineer | HIGH | Deployed | Frame as "containerized ML-ready Python services on Kubernetes" |
| Data Platform/Infra | HIGH | Built & operated | Lead with infrastructure automation; K8s + CI/CD is the core signal |

---

### SW-4: B2B Data Products, Stakeholder Analytics & Automation
**Significance:** Demonstrates the bridge between engineering and business — delivering actionable data to stakeholders while automating operations. Key for Analytics Engineer positioning; supporting for others.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | MED | Delivered | Supporting bullet — shows stakeholder-facing breadth; pair with SW-2 |
| Analytics Engineer | HIGH | Delivered | LEAD bullet for this role type — emphasize B2B stakeholder impact and dashboard delivery |
| ML/AI Engineer | LOW | — | Omit or condense; not core ML signal |
| Data Platform/Infra | LOW | — | Omit; not infrastructure-focused |

---

### SW-5: Security Champion — 2025/2026 (team role, NOT an award)
**Significance:** Modest. This is a **rotating team role** (security point of contact), held for **2025/2026 only** — corrected 2026-07-27. It is not an award, not a distinction, and not "3 consecutive years" (an earlier version of this file claimed that; it was wrong).

**DEFAULT: OMIT.** Include only when the JD explicitly requires security or DevSecOps experience. Never place under Awards/Honors.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| All role types (JD silent on security) | OMIT | — | Leave it out — it costs a bullet slot and reads as padding |
| Any role type (JD explicitly requires security/DevSecOps) | MED | Serve as | State plainly as a team role for 2025/2026; cite the 100h training + assessment, claim no more |

---

### SW-6: PySpark Backend Engineering
**Significance:** Confirms Big Data / distributed processing capability at Staff level. Differentiates from Python-only data engineers when JD requires Spark.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| All role types | MED | Applied | Roll into skills section unless JD explicitly requires PySpark — then elevate to bullet |
| Data Platform/Infra | MED | Applied | Include as distributed processing signal |

---

## BOSCH ACHIEVEMENTS

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### BS-1: ML Inference Containerization in 24/7 Production (Defect Management Domain)
**Significance:** Deploying ML models into a continuous, uninterruptible semiconductor production line is a uniquely high-stakes MLOps achievement — far beyond typical "model trained in notebook" experience. The defect management domain (image-based wafer defect classification) adds semiconductor industry specificity — a rare combination of MLOps depth + semiconductor domain expertise.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | HIGH | Containerized | Frame as data pipeline + ML integration — "production ML as part of data infrastructure" |
| Analytics Engineer | MED | Containerized | For semi industry JDs: include with defect management domain framing — "automated defect classification analytics" |
| ML/AI Engineer | HIGH | Containerized | FLAGSHIP bullet — lead with "24/7 production ML", automated inference, K8s orchestration, defect detection |
| Data Platform/Infra | HIGH | Containerized | Lead with Docker/K8s/Ansible infrastructure; de-emphasize ML domain |
| **Semiconductor JDs** | HIGH | Containerized | Lead with defect management domain — "automated image-based defect classification for 300mm fab"; this is the differentiating signal for semi industry applications |

**Overclaiming warning:** "Significantly reducing manual workload" is the claim — employer Zeugnis says "enabling fully automated image classification". Safe to use. No percentage available — do not invent.

---

### BS-2: Data Services Over OracleDB and Hadoop/ImpalaSQL
**Significance:** Multi-language (Python/Java/C#) data service development over enterprise-grade databases in a high-throughput manufacturing environment confirms broad data engineering depth and platform-agnostic capability. For semiconductor JDs: these data services fed Defect Management, Parameter Testing, and Process Analysis teams directly.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | HIGH | Built | Lead with data service breadth; multiple languages + Oracle + Hadoop = enterprise DE depth |
| Analytics Engineer | MED | Built | Frame as "supplying analysis teams with structured data access" |
| Analytics Engineer (semi JD) | HIGH | Built | Lead with domain: "supplying defect management and parameter testing teams with on-demand data and insights" |
| ML/AI Engineer | MED | Built | Frame as "data layer enabling ML model inputs" |
| Data Platform/Infra | HIGH | Built | Lead with Oracle + Hadoop infrastructure combination |

---

### BS-3: Application Owner — Analytics Platforms
**Significance:** Application Owner is a well-understood seniority signal in German/Swiss tech companies — it means owning the system's lifecycle, not just writing code. SLO definition + training + stakeholder management = staff-level maturity.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | HIGH | Owned | ALWAYS include — clearest seniority signal from Bosch period |
| Analytics Engineer | HIGH | Owned | Frame as "enabling reliable data access for analysis teams" |
| ML/AI Engineer | MED | Owned | Include as operational ownership signal |
| Data Platform/Infra | HIGH | Owned | Frame around SLA + platform reliability angle |

---

### BS-4: ELK Stack PoC — Anomaly Detection & Monitoring
**Significance:** Self-initiated observability work beyond the core job scope — demonstrates initiative and infrastructure curiosity. ELK + Kafka + Grafana/Prometheus is a recognizable modern observability stack.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | MED | Delivered | Supporting bullet — shows platform breadth; include if space allows |
| Analytics Engineer | LOW | — | Omit |
| ML/AI Engineer | MED | Delivered | Frame as anomaly detection ML application |
| Data Platform/Infra | HIGH | Delivered | Lead observability stack angle — ELK + Prometheus + Grafana |

**Note:** CV-2 only. Include when 2-page resume has budget; always in 5-page CV.

---

### BS-5: Tibco Spotfire C# Extensions
**Significance:** Minor — niche BI tooling signal. Only relevant if JD specifically mentions Spotfire or C#-based analytics tooling.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| All role types | LOW | — | Omit from resume; include in skills taxonomy only |
| Analytics Engineer | LOW | Developed | Include only if JD explicitly names Spotfire |

---

## FRAUNHOFER ACHIEVEMENTS

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### FC-1: SCEDAS Development + CI/CD Pipeline Introduction
**Significance:** Independently introduced CI/CD to a research team (no prior automation existed) — strong initiative signal. SCEDAS development confirms C# / .NET / SQL depth. The CI/CD angle is more valuable for target roles than the DSS domain.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | MED | Established (for CI/CD) | Lead with CI/CD independence; SCEDAS is context |
| Analytics Engineer | LOW | — | Omit |
| ML/AI Engineer | LOW | — | Omit |
| Data Platform/Infra | MED | Established | Lead with pipeline automation initiative |

---

### FC-2: ARTUS — ML/NLP for Sea Rescue Transcription
**Significance:** Applied ML/NLP in a safety-critical domain as part of a named research project at a leading European applied research institute. Confirms early ML/NLP exposure (pre-Bosch) — establishes ML thread across career.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | MED | Contributed | Supporting signal — shows ML breadth from earlier career |
| Analytics Engineer | LOW | — | Omit |
| ML/AI Engineer | HIGH | Contributed | Include — establishes NLP / ML research background; pair with Bosch ML deployment |
| Data Platform/Infra | LOW | — | Omit |

**Verb:** ALWAYS use "Contributed" — this was research team work, not sole development.

---

### FC-3: MISSION — Maritime Microservice Platform
**Significance:** Hands-on microservices + Docker in 2018–2019 — predates the containerization wave. Shows early adoption of modern architecture patterns.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | MED | Built | Early Docker/microservice signal — pair with FC-1 |
| Analytics Engineer | LOW | — | Omit |
| ML/AI Engineer | LOW | — | Omit |
| Data Platform/Infra | MED | Built | Early containerization signal |

---

### FC-4: Predictive Maintenance Grant Contribution
**Significance:** Minimal — contributed to a grant proposal. Include only in CL for research-adjacent roles.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| All roles | LOW | Contributed | CL mention only — not a resume bullet |

---

## VIZRT ACHIEVEMENTS

---

### VZ-1: Distributed Video Transcoding Backend
**Significance:** Python + C++ in a distributed backend for a globally-deployed broadcast platform (CNN, BBC, Al Jazeera scale). Confirms systems programming capability and international team experience.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | MED | Engineered | Include as backend systems depth signal |
| Analytics Engineer | LOW | — | Omit |
| ML/AI Engineer | LOW | — | Omit |
| Data Platform/Infra | MED | Engineered | Include for distributed systems signal |

---

### VZ-2: Test Automation + CI/CD Quality Gates Integration
**Significance:** Owning the quality gate mechanism in a CI/CD pipeline for production broadcast software — more than just test writing. Shortening feedback loop and time-to-market at a company serving global broadcasters.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | MED | Built | Include as CI/CD quality ownership signal |
| Analytics Engineer | LOW | — | Omit |
| ML/AI Engineer | LOW | — | Omit |
| Data Platform/Infra | MED | Built | Include for CI/CD depth; quality gates framing |

**Note:** For tight 2-page budgets, combine VZ-1 and VZ-2 into a single 2L bullet for Vizrt position.

---

## GENERALI ACHIEVEMENTS

---

### GN-1: BDD Technical Ownership & Team Evangelism
**Significance:** Introduced a practice (BDD) to an organization and then held technical ownership of it — demonstrates initiative, technical leadership, and knowledge-transfer capability. Strongest signal from Generali period.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| Staff/Senior Data Engineer | MED | Introduced | Include as initiative + technical leadership thread from earlier career |
| Analytics Engineer | LOW | — | Omit |
| ML/AI Engineer | LOW | — | Omit |
| Data Platform/Infra | LOW | — | Omit |

---

### GN-2: UIPath RPA POC
**Significance:** Early RPA experience — niche signal. Only relevant for roles explicitly targeting automation engineering.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| All roles | LOW | Developed | Omit from resume; include in CV if space |

---

### GN-3 & GN-4: Java/J2EE Development + IBM ODM
**Significance:** Early-career Java and enterprise software context. Not differentiating at current career stage.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| All roles | LOW | — | CV only — early career context |

---

## CAPGEMINI ACHIEVEMENTS

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### CA-1: GUI Test Automation — Transport Logistics Client
**Significance:** Establishes the test automation thread from day one of career. Zeugnis rates "vollsten Zufriedenheit" (top tier) despite being only 6 months. Historical context only at current career stage.

| Role Type | Priority | Lead Verb | Framing Angle |
|-----------|----------|-----------|---------------|
| All roles | LOW | Implemented | CV only — do not include on 2-page resume |

---

## Master Priority Matrix (Cross-Role)

| Achievement | Staff/Senior DE | Analytics Eng | ML/AI Eng | Data Platform/Infra |
|-------------|----------------|---------------|-----------|---------------------|
| SW-1 AWS Migration | HIGH | HIGH | MED | HIGH |
| SW-2 Component Owner | HIGH | HIGH | MED | HIGH |
| SW-3 K8s + GitLab | HIGH | MED | HIGH | HIGH |
| SW-4 B2B Products | MED | HIGH | LOW | LOW |
| SW-5 Security Champion | LOW | LOW | LOW | LOW |
| SW-6 PySpark | MED | LOW | MED | MED |
| BS-1 ML Inference | HIGH | LOW | HIGH | HIGH |
| BS-2 Data Services | HIGH | MED | MED | HIGH |
| BS-3 App Owner | HIGH | HIGH | MED | HIGH |
| BS-4 ELK PoC | MED | LOW | MED | HIGH |
| FC-1 SCEDAS + CI/CD | MED | LOW | LOW | MED |
| FC-2 ARTUS ML/NLP | MED | LOW | HIGH | LOW |
| FC-3 MISSION Microsvcs | MED | LOW | LOW | MED |
| VZ-1 Video Backend | MED | LOW | LOW | MED |
| VZ-2 CI/CD Quality Gates | MED | LOW | LOW | MED |
| GN-1 BDD Ownership | MED | LOW | LOW | LOW |
| GN-2 UIPath RPA | LOW | LOW | LOW | LOW |
