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# Skills Taxonomy — Dennis Thiessen
# Skills Taxonomy — Evidence-First
> Generated: 2026-03-28
> Sources: All 10 extractions + 6 experience files
> Use this file when populating the Technical Skills section of resume/CV.
> Canonical authority: `resume_builder/canonical/claims.json`.
> This file helps select and group skills; it may not promote a skill beyond its canonical evidence level.
---
## Evidence Levels
## Summary Stats
| Level | Meaning | Output rule |
|---|---|---|
| Production — current | Used in current professional delivery | May appear plainly when relevant |
| Production — historical | Shipped professionally, but not current | Include with role/date context when recency matters |
| Hands-on — current | Used directly, but without verified production ownership | Use precise verbs such as used, configured or integrated |
| Project / proof of concept | Used in a bounded PoC | Label the PoC; never imply platform-scale operation |
| Certification / coursework | Learned through formal study | Keep in certification context; not professional experience |
| Unverified / never used | No reliable evidence | Do not include |
- **Total unique skills:** 65+
- **Proficiency levels:** Expert (daily use, owned systems) | Proficient (shipped work, comfortable teaching) | Familiar (used in project, not current)
- **Certification-backed skills:** AWS (SAA cert + Udacity DataEng), Software Architecture (iSAQB), AI/ML (Udacity AI for Trading, IBM AI Engineering)
Do not use Expert/Proficient/Familiar labels in resumes. Evidence and recency are more useful than self-ratings.
---
## Current Production Core
## Category 1: Programming Languages
| Skill | Evidence | Typical use |
|---|---|---|
| Python | Swisscom pipelines/apps; prior Bosch/Vizrt work | Always for data/platform roles |
| SQL | Swisscom and prior data roles | Always for data roles |
| PySpark | Swisscom current work | When distributed processing is relevant |
| Apache Kafka | Swisscom production ingestion | Data/event-driven roles |
| Apache Airflow | Swisscom AWS migration scope | Orchestration/data roles |
| AWS | Swisscom production work; SAA certification | AWS-relevant roles |
| S3, Glue, Athena, Iceberg, Redshift | Swisscom owned-domain migration/data products | Name only relevant services |
| CloudFormation / IaC | Swisscom production provisioning | Say CloudFormation; never substitute Terraform |
| Kubernetes, Docker | Swisscom application delivery; Bosch ML integration | Production platform/MLOps roles |
| GitLab CI/CD | Swisscom delivery | Platform and engineering roles |
| Oracle, Teradata | Swisscom pipelines | Data roles when relevant |
| Skill | Proficiency | Evidence | Resume Weight |
|-------|-------------|----------|---------------|
| Python | Expert | Swisscom (pipelines, apps), Bosch (data services), Fraunhofer (ML/NLP), Vizrt (backend + tests) | HIGH |
| SQL (multi-dialect) | Expert | All positions — Oracle, Impala, Teradata, MS SQL, Postgres, MySQL | HIGH |
| PySpark | Proficient | Swisscom Staff level (LinkedIn confirmed) | HIGH |
| Java | Proficient | Fraunhofer (SCEDAS, MISSION), Bosch (data services), Generali (J2EE), Capgemini | MED |
| C# | Proficient | Bosch (data services, Spotfire extensions), Fraunhofer (SCEDAS) | MED |
| JavaScript / TypeScript | Proficient | Fraunhofer (MISSION, Express.js), CV skills list | MED |
| C++ | Proficient | Vizrt (backend transcoding), Generali (CV) | LOW |
| VBA | Familiar | Student assistant role (Bundeswehr Uni, 2013) — very minor | LOW |
## Historical Production Evidence
---
| Skill | Evidence | Constraint |
|---|---|---|
| Java | Bosch, Fraunhofer, Generali | Historical; do not imply current daily use |
| C# | Bosch and Fraunhofer | Historical; strong when Spotfire/.NET is relevant |
| C++ | Vizrt distributed backend | Limited historical evidence |
| JavaScript / Express.js | Fraunhofer MISSION | Historical and bounded; TypeScript is unverified |
| Hadoop / Impala | Bosch data services | Historical production context |
| Ansible | Bosch ML integration | Historical production context |
| Jenkins | Fraunhofer and Generali | Historical production context |
| BDD, Selenium, JBehave | Generali | Earlier-career testing evidence |
| TIBCO Spotfire | Bosch co-ownership and C# extensions | Preserve co-ownership |
## Category 2: Data Engineering & Pipelines
## ML, AI and Observability
| Skill | Proficiency | Evidence | Resume Weight |
|-------|-------------|----------|---------------|
| ETL/ELT design & operation | Expert | Swisscom (component owner), Bosch (data services) | HIGH |
| Apache Kafka | Expert | Swisscom (ingestion pipelines), Bosch (ELK PoC) | HIGH |
| Apache Airflow | Proficient | Swisscom (AWS migration stack) | HIGH |
| SAP BODS | Proficient | Swisscom (legacy ETL) | MED |
| Teradata DWH | Proficient | Swisscom (DWH architecture + operation) | MED |
| Hadoop / ImpalaSQL | Proficient | Bosch (data services over Hadoop) | MED |
| Data modeling | Proficient | Swisscom (data products), Bosch (pipeline design) | MED |
| SQL performance tuning | Proficient | CV (explain plans, indexes, partitions) | MED |
| Apache Spark / PySpark | Proficient | Swisscom (big data processing) | HIGH |
| dbt | Not confirmed | Not in any extraction — do not claim | — |
| Skill | Evidence level | Safe framing |
|---|---|---|
| ML inference deployment | Production — historical | Integrated containerized inference into a 24/7 Bosch fab |
| Image classification | Production application context | Worked on inference integration; model-training ownership not verified |
| MLOps | Bounded production evidence | Use only when defined as deployment/operation, not full model lifecycle |
| NLP / speech recognition | Research-project contribution | Contributed components at Fraunhofer; no publication/model ownership |
| ELK, Kafka anomaly detection | Proof of concept | Always retain the PoC label |
| Grafana, Prometheus, Loki | Proof-of-concept/monitoring context | Do not imply enterprise observability ownership |
| LiteLLM | Hands-on — current | LLM API gateway use/integration; no serving-platform ownership |
| Domain-grounded assistants/custom GPTs | Hands-on — current | Configured with curated knowledge; no fine-tuning or formal evaluation |
| Copilot, Kiro | Hands-on — current | AI-assisted engineering tools, not LLM product engineering |
---
## Certification-Only Signals
## Category 3: Cloud & Infrastructure
| Skill | Evidence |
|---|---|
| TensorFlow / Keras | IBM AI Engineering coursework |
| PyTorch | Coursework/personal evidence only; verify before listing outside certification context |
| Spark ML | Coursework context only unless professional evidence is added |
| AI for Trading / quantitative ML | Udacity/WorldQuant Nanodegree |
| Skill | Proficiency | Evidence | Resume Weight |
|-------|-------------|----------|---------------|
| AWS (overall) | Proficient | Swisscom (migration), AWS SAA cert (2024), Udacity DataEng cert (2026) | HIGH |
| AWS S3 | Proficient | Swisscom AWS migration | HIGH |
| AWS Glue | Proficient | Swisscom AWS migration | HIGH |
| AWS Athena | Proficient | Swisscom AWS migration (with Apache Iceberg table format) | HIGH |
| AWS Glue (Jobs + Tables) | Proficient | Swisscom — Glue jobs for ETL + Glue Data Catalog / Glue Tables | HIGH |
| Apache Iceberg | Proficient | Swisscom — S3 + Athena with Iceberg table format (open table format, time-travel, schema evolution) | HIGH |
| AWS Redshift | Proficient | Swisscom AWS migration | HIGH |
| AWS Lambda | Proficient | Swisscom AWS migration | MED |
| AWS Step Functions | Proficient | Swisscom AWS migration | MED |
| AWS CloudFormation | Proficient | Swisscom — IaaS, infrastructure provisioning as code | HIGH |
| Kubernetes (K8s) | Expert | Swisscom (Python app deployment), Bosch (ML inference orchestration) | HIGH |
| Docker | Expert | Bosch (ML containerization, ELK PoC), Fraunhofer (MISSION), Swisscom | HIGH |
| Ansible | Proficient | Bosch (ML orchestration) | MED |
| GitLab CI/CD | Proficient | Swisscom (confirmed Zeugnis) | HIGH |
| Jenkins | Proficient | Fraunhofer (independently set up), Generali (BDD build jobs) | MED |
| CI/CD (general) | Expert | Swisscom, Fraunhofer, Vizrt, Generali — cross-position | HIGH |
| IaC (Infrastructure as Code) | Proficient | Swisscom — AWS CloudFormation confirmed by user | HIGH |
| DevSecOps | Proficient | Swisscom Security Champion ×3 (2023–2026), 100h training | MED |
## Forbidden Until New Evidence Is Added
---
- LangChain, LangGraph, LlamaIndex, AutoGen, CrewAI or Semantic Kernel
- Azure, Azure ML, Azure OpenAI or AKS
- GCP, BigQuery, Dataflow or Flume hands-on experience
- Terraform
- Formal model or LLM evaluation
- LLM fine-tuning, red-teaming or model-training ownership
- FastAPI, Flask or Django
- TypeScript
- Petabyte-scale ownership
## Category 4: Databases & Storage
## Certifications
| Skill | Proficiency | Evidence | Resume Weight |
|-------|-------------|----------|---------------|
| Oracle DB | Expert | Swisscom (Fulfillment pipelines), Bosch (data services), Generali (web portal) | HIGH |
| Teradata | Proficient | Swisscom (DWH target, architecture) | MED |
| MS SQL Server | Proficient | Fraunhofer (SCEDAS — Entity Framework) | LOW |
| PostgreSQL | Familiar | CV skills list | LOW |
| MySQL | Familiar | CV skills list, RiskAhead project | LOW |
| SQLite | Familiar | Fraunhofer (MISSION microservices) | LOW |
| Hadoop / Impala | Proficient | Bosch (ImpalaSQL data services) | MED |
| Certification | Issuer | Year/status |
|---|---|---|
| AWS Certified Solutions Architect — Associate | AWS | 2024; active to Sep 2027 |
| Data Engineering with AWS Nanodegree | Udacity | 2026 |
| iSAQB CPSA — Foundation | iSAQB | 2016; no expiry |
| ITIL Foundation | PEOPLECERT / AXELOS | 2016; no expiry |
| AI for Trading Nanodegree | Udacity / WorldQuant | 2021 |
| IBM AI Engineering Specialization | IBM / Coursera | Completion year not recorded |
---
The Swisscom Security Champion assignment is not a certification and does not belong in this table.
## Category 5: ML & AI
## Resume Grouping
| Skill | Proficiency | Evidence | Resume Weight |
|-------|-------------|----------|---------------|
| ML inference deployment | Proficient | Bosch (Docker/K8s in 24/7 fab — primary responsibility) | HIGH |
| Image classification | Proficient | Bosch (automated quality monitoring in semiconductor fab) | MED |
| NLP / Speech recognition | Familiar | Fraunhofer ARTUS research project (contributing role) | MED |
| PyTorch | Familiar | CV skills list | LOW |
| Scikit-learn | Familiar | CV skills list | LOW |
| Pandas / NumPy | Proficient | CV (data analysis, pipeline work) | MED |
| Matplotlib / Plotly | Proficient | CV (data visualization, dashboards) | LOW |
| MLOps (general) | Proficient | Bosch (full ML lifecycle: containerize → deploy → monitor in production) | HIGH |
| AI for Trading / Quant ML | Familiar | Udacity AI for Trading Nanodegree (2021) — personal study, not professional | LOW |
| TensorFlow / Keras | Familiar | IBM AI Engineering Specialization (Coursera) | LOW |
| Apache Spark ML | Familiar | IBM AI Engineering (Spark ML course) | LOW |
Use 4--6 compact lines, selected for the JD. A normal International Tech grouping is:
**Proficiency note:** For ML/AI roles, frame Bosch ML deployment as primary evidence. NLP/ARTUS and the Udacity/IBM certs as supporting signals. Do not overstate ML modeling depth — the core strength is ML *infrastructure and deployment*, not research.
1. Languages: Python, SQL; selected historical languages only when required.
2. Data: Kafka, Airflow, PySpark, Oracle/Teradata, data products and governance.
3. Cloud/platform: AWS services, CloudFormation, Kubernetes, Docker, GitLab CI/CD.
4. ML/operations: ML inference deployment and bounded observability evidence.
5. Certifications: one line, only the most relevant credentials.
---
## Category 6: Testing & Quality Engineering
| Skill | Proficiency | Evidence | Resume Weight |
|-------|-------------|----------|---------------|
| Test automation | Expert | Capgemini, Generali, Vizrt — consistent across 3 positions | MED (earlier career) |
| BDD (Behaviour-Driven Development) | Proficient | Generali — introduced PoC, held technical ownership | MED |
| Serenity-BDD / JBehave | Proficient | Generali (confirmed Zeugnis) | LOW |
| Selenium | Proficient | Generali (UI test automation) | LOW |
| pytest | Proficient | CV skills list | MED |
| TDD | Proficient | Capgemini, Generali (confirmed) | LOW |
| HP Quality Center / ALM | Familiar | Capgemini (Zeugnis confirmed) | LOW |
| UIPath RPA | Familiar | Generali (POC developer, confirmed Zeugnis + LinkedIn) | LOW |
| Camunda BPMN | Familiar | Generali (LinkedIn confirmed) | LOW |
| Quality gates (CI/CD) | Proficient | Vizrt (CI/CD integration), Fraunhofer (Jenkins quality gates) | MED |
---
## Category 7: Observability, Monitoring & DevOps Tooling
| Skill | Proficiency | Evidence | Resume Weight |
|-------|-------------|----------|---------------|
| ELK Stack (Elasticsearch/Logstash/Kibana) | Proficient | Bosch (anomaly detection PoC — primary developer) | MED |
| Grafana | Proficient | Bosch (monitoring dashboards) | MED |
| Prometheus | Proficient | Bosch (metrics) | MED |
| Loki | Familiar | Bosch (log aggregation, part of PoC) | LOW |
| Git | Expert | All positions | HIGH |
| Agile / Scrum | Proficient | Swisscom (confirmed Zeugnis — backlog, sprint planning, Product Owner collaboration) | MED |
| Tibco Spotfire | Familiar | Bosch (C# extensions, LinkedIn confirmed) | LOW |
---
## Category 8: Frameworks & APIs
| Skill | Proficiency | Evidence | Resume Weight |
|-------|-------------|----------|---------------|
| Flask / FastAPI / Django | Proficient | CV skills list | MED |
| Express.js | Familiar | Fraunhofer MISSION (microservices) | LOW |
| Entity Framework (.NET) | Proficient | Fraunhofer SCEDAS | LOW |
| Spring Boot | Familiar | Generali (Dispatcher PoC, Apache Camel) | LOW |
| Apache Camel | Familiar | Generali (Dispatcher PoC) | LOW |
| SQLAlchemy | Familiar | CV skills list | LOW |
| Swagger / OpenAPI | Familiar | CV skills list | LOW |
---
## Category 9: Domain Knowledge
| Domain | Depth | Source | Resume Weight |
|--------|-------|--------|---------------|
| Telecom / Enterprise data platforms | Proficient | Swisscom (2+ years, current) | HIGH |
| Semiconductor manufacturing / Industry 4.0 | Proficient | Bosch (3 years) — data domains: Defect Management, Semiconductor Parameter Testing, Process Analysis, Image-based Quality Inspection | MED |
| Maritime logistics | Familiar | Fraunhofer CML (1 year research) | LOW |
| Broadcast technology | Familiar | Vizrt (1 year) | LOW |
| Insurance IT / Business process automation | Familiar | Generali (2 years) | LOW |
| Security / DevSecOps | Proficient | Swisscom Security Champion ×3 | MED |
| Blockchain / Web3 | Familiar | Personal — RPC APIs, basic Solidity, Kraken since 2017 | LOW (bonus only) |
---
## Category 10: Certifications (Skills Signals)
| Certification | Issuer | Year | Active | Resume Weight |
|--------------|--------|------|--------|---------------|
| AWS Certified Solutions Architect – Associate | AWS | 2024 | Yes (until Sep 2027) | HIGH |
| Data Engineering with AWS (Nanodegree) | Udacity | 2026 | Yes | HIGH |
| iSAQB Certified Professional for Software Architecture — Foundation Level | iSAQB | 2016 | Yes (no expiry) | MED |
| ITIL® Foundation Certificate in IT Service Management | PEOPLECERT / AXELOS | 2016 | Yes (no expiry) | LOW |
| AI for Trading Nanodegree | Udacity / WorldQuant | 2021 | Yes | LOW (niche) |
| Swisscom Security Champion | Swisscom (internal) | 2023–2026 | Active | MED (as bullet, not cert line) |
| IBM AI Engineering Specialization | IBM / Coursera | — | Yes | LOW |
---
## Skills Config Guide (for resume generation)
Refers to `config.md` skills layout: **4-3-2-2-2** (resume) or **4-4-3-3-3** (CV).
### Suggested Resume Skills Groups (5 groups)
| Group | Label | Skills to include |
|-------|-------|------------------|
| 1 (4 lines) | Languages & Data | Python, PySpark, SQL (Oracle · Impala · Teradata · Postgres), Java · C# |
| 2 (3 lines) | Cloud & Infra | AWS (S3 · Glue · Athena · Redshift · Airflow), Kubernetes · Docker · Ansible, GitLab CI/CD · Jenkins |
| 3 (2 lines) | Pipelines & Platforms | Kafka · Airflow · SAP BODS · Hadoop, Teradata DWH · ETL/ELT design |
| 4 (2 lines) | ML & Observability | ML inference deployment · MLOps · PyTorch · Scikit-learn, ELK Stack · Grafana · Prometheus |
| 5 (2 lines) | Certifications | AWS Certified Solutions Architect – Associate (active), iSAQB CPSA Foundation · ITIL v3 · Data Engineering with AWS (Udacity) |
**Adjust per JD:** For ML/AI roles, swap group 4 to lead with ML; for Platform/Infra roles, expand cloud group. The cert line (group 5) is fixed per `config.md`.
Never add a skill only to mirror a JD. Every listed skill must have a canonical evidence level and an interview-ready example.