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%	HEADER
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\name{Dennis Thiessen, M.Eng.}
\address{\href{https://linkedin.com/in/dennis-thiessen}{LinkedIn}}
\address{dennis@thiessen.io \\ +41 795 955 585}
\address{Bern, Switzerland $\vert$ German citizen $\vert$ Open to relocation to Zurich}
\address{{Staff Data Engineer $\vert$ NLP \& Computer Vision $\cdot$ Airflow $\cdot$ Agentic Workflows $\vert$ AWS $\cdot$ Python}}


\begin{document}

\vspace{-0.15cm}

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%	SUMMARY
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\begin{rSection}{Summary}
Data and ML engineer with 10+ years building production data pipelines --- Fraunhofer \textbf{NLP} research, Bosch \textbf{computer vision} in a 24/7 semiconductor fab, and Swisscom telecom-scale ETL at petabyte scale. At Swisscom, own the \textbf{AWS} data platform (\textbf{Airflow}, Glue, Athena, \textbf{PySpark}) processing large-scale data for ML and analytics. Expert in \textbf{Python}; designed and implemented agentic workflows using \textbf{LangChain} and custom GPTs to automate engineering processes. M.Eng.\ (thesis grade 1.0) in neural network-based fault diagnosis. German native, fluent English.
\end{rSection}
\vspace{-0.15cm}

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%	TECHNICAL SKILLS — Format C, 5 groups (4-3-2-2-2 = 13 lines)
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\begin{rSection}{Technical Skills}

\begin{skillgroup}{Machine Learning \& AI}
\skilldash{\textbf{NLP}, \textbf{computer vision}, deep learning, ML inference deployment, generative AI / LLMs, \textbf{agentic workflows}}
\skilldash{\textbf{LangChain}, custom GPT development, \textbf{PyTorch}, TensorFlow/Keras (IBM cert), Scikit-learn, Spark ML}
\skilldash{Multi-domain data processing (tabular, image, text, video), speech recognition, image classification, anomaly detection}
\skilldash{Statistical modeling, time-series analysis, quantitative ML, data quality, model training support, data preprocessing}
\skilldash{Human-in-the-loop data workflows, ML dataset curation, annotation pipeline support, data quality validation}
\skilldash{Synthetic data preprocessing, multi-modal dataset pipelines, model training data at petabyte scale}
\end{skillgroup}

\begin{skillgroup}{Data Engineering \& Orchestration}
\skilldash{\textbf{Apache Airflow}, Apache Kafka, \textbf{PySpark} / Apache Spark, \textbf{Databricks}, Apache Iceberg, Hadoop/ImpalaSQL}
\skilldash{\textbf{AWS} (S3, Glue, Athena/Iceberg, Redshift, Lambda, \textbf{Airflow}, CloudFormation), Teradata DWH, OracleDB}
\skilldash{ETL/ELT pipeline design, data modeling, data governance, SQL (Oracle, Impala, Teradata, Postgres), NoSQL}
\skilldash{Data pipeline monitoring, SLA compliance management, batch and stream processing, data lineage, data versioning}
\end{skillgroup}

\begin{skillgroup}{Cloud \& Container Infrastructure}
\skilldash{\textbf{Docker}, \textbf{Kubernetes}, Ansible, GitLab CI/CD, Jenkins, Infrastructure as Code, DevSecOps, build automation}
\skilldash{ELK Stack (Elasticsearch, Logstash, Kibana), Grafana, Prometheus, Loki, monitoring, log aggregation, alerting}
\skilldash{AWS Lambda, CloudWatch, ECR, ECS, Step Functions, SQS, SNS, event-driven architectures, serverless}
\end{skillgroup}

\begin{skillgroup}{Programming Languages \& Frameworks}
\skilldash{\textbf{Python} (expert), \textbf{Java} (strong), C++, C\#, JavaScript, SQL, Flask/FastAPI, Express.js, .NET/Entity Framework}
\skilldash{Pandas, NumPy, SQLAlchemy, Matplotlib, Bash, Git, pytest, Agile/Scrum, technical documentation}
\skilldash{Jupyter Notebooks, dbt, shell scripting, code review, unit testing, software design patterns}
\end{skillgroup}

\begin{skillgroup}{Certifications}
\skilldash{AWS Certified Solutions Architect -- Associate (2024, active), Data Engineering with AWS (Udacity, 2026)}
\skilldash{IBM AI Engineering Specialization, AI for Trading Nanodegree (Udacity, 2021), iSAQB CPSA-F (2016)}
\end{skillgroup}

\end{rSection}
\vspace{-0.15cm}

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%	PROFESSIONAL EXPERIENCE
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\begin{rSection}{Professional Experience}

% --- Swisscom (Oct 2023 -- Present) — 4 bullets: SW-2, SW-1, SW-GenAI, SW-4 ---
\begin{rSubsection}{ML Data Pipelines, Agentic Workflows \& Cloud Infrastructure}{\textcolor{black!60}{Oct 2023 -- Present}}{Staff Data, Analytics \& AI Engineer, Swisscom (Schweiz) AG}{Bern, Switzerland}
\item Owned Fulfillment and Product Analysis ETL pipelines (Oracle, \textbf{Kafka} to Teradata DWH in \textbf{Python}) as component owner, enforcing data governance and SLA compliance for business-critical production data flows at scale.
\item Migrated legacy Teradata/Oracle ETL stack to \textbf{AWS} (S3, Glue, \textbf{Airflow}, Athena/Iceberg, Redshift, CloudFormation), enabling scalable serverless data processing for ML and analytics at telecom scale.
\item Designed and implemented agentic \textbf{LangChain} workflows with domain-specific GPT knowledge bases at Swisscom, automating code review, documentation, and pipeline troubleshooting to cut manual engineering effort.
\item Delivered self-service data products, analyses and dashboards for B2B stakeholders; drove \textbf{Python} process automation and 3rd-level root cause analysis to maintain reliable data platform operations.
\item Deployed and operated \textbf{Python} data applications on \textbf{Kubernetes} clusters with GitLab CI/CD automation, owning the containerized delivery lifecycle from build and test to production rollout in an agile DevOps team.
\item Applied \textbf{PySpark} and distributed computing within the Swisscom Data Lake platform, extending \textbf{Python} pipeline capabilities to large-scale batch workloads for Fulfillment and Product Analysis data.
\end{rSubsection}

% --- Bosch (Feb 2020 -- Dec 2022) — 4 bullets: BS-1, BS-2, BS-3, BS-4 ---
\begin{rSubsection}{Computer Vision \& ML Deployment in Semiconductor Manufacturing}{\textcolor{black!60}{Feb 2020 -- Dec 2022}}{(Senior) Data \& ML Engineer, Robert Bosch Semiconductor Manufacturing}{Dresden, Germany}
\item Deployed \textbf{ML inference} (\textbf{Docker}, Kubernetes, Ansible) into a 24/7 semiconductor fab, automating \textbf{computer vision}-based defect classification and replacing manual inspection across 300mm production lines.
\item Built data services in \textbf{Python}, Java and C\# over OracleDB and Hadoop/ImpalaSQL, supplying semiconductor analysis teams with structured access to defect management and process optimization data.
\item Served as Application Owner for the semiconductor analytics suite and upstream data pipelines, defining SLOs, managing vendors, and delivering user training and documentation across fab operations teams.
\item Delivered anomaly detection PoC using ELK Stack and \textbf{Kafka} (\textbf{Docker}) with Grafana, Prometheus and Loki monitoring, demonstrating centralized real-time alerting for 24/7 semiconductor infrastructure.
\item Built C\# analytical extensions for Tibco Spotfire at Bosch Semiconductor, delivering custom data visualization and querying capabilities to support semiconductor process engineers in wafer defect analysis.
\end{rSubsection}

% --- Fraunhofer (Sep 2018 -- Oct 2019) — 3 bullets: FC-2, FC-1, FC-3 ---
\begin{rSubsection}{Applied NLP/ML Research \& Software Engineering}{\textcolor{black!60}{Sep 2018 -- Oct 2019}}{Research Software Engineer, Fraunhofer-Center for Maritime Logistics CML}{Hamburg, Germany}
\item Contributed \textbf{ML and NLP} components to ARTUS, a Fraunhofer research project for automatic sea rescue speech transcription that combined speech recognition and machine learning for a safety-critical maritime domain.
\item Set up Jenkins CI/CD pipeline with quality gates independently, introducing build automation to the research team; developed SCEDAS crew scheduling software (C\#, .NET, MS SQL Server, Entity Framework).
\item Built microservices (Express.js, \textbf{Docker}, SQLite) for MISSION, a Fraunhofer research platform for maritime data exchange between logistics stakeholders including ports, operators, and research partners.
\item Contributed to a Fraunhofer CML research grant proposal for ML-based predictive maintenance of maritime equipment, applying time-series analysis and ML to equipment condition data and maintenance timing prediction.
\end{rSubsection}

% --- Vizrt (Jul 2017 -- May 2018) — 2 bullets: VZ-1, VZ-2 ---
\begin{rSubsection}{Broadcast Video Data Processing \& Python/C++ Backend Engineering}{\textcolor{black!60}{Jul 2017 -- May 2018}}{DevOps Engineer, Vizrt}{Bergen, Norway}
\item Engineered distributed video transcoding backend components in \textbf{Python} and C++ for Vizrt's broadcast platform, processing A/V data at scale for global media customers including CNN, BBC, and Al Jazeera.
\item Built automated integration and unit test suite for A/V streaming (\textbf{Python}) and integrated quality gates into CI/CD, which shortened the feedback loop for new features and raised overall release quality.
\end{rSubsection}

% --- Generali (May 2015 -- Jun 2017) — 2 bullets: GN-1, GN-3 ---
\begin{rSubsection}{Test Automation \& BDD Technical Ownership}{\textcolor{black!60}{May 2015 -- Jun 2017}}{IT Consultant, Generali Deutschland Informatik Services}{Hamburg, Germany}
\item Introduced BDD test automation to Generali (Serenity-BDD, Selenium, JBehave), running the initial PoC and taking technical ownership; trained project teams and presented the methodology across the Java Community.
\item Developed UIPath RPA proofs of concept at Generali GDIS and served as internal RPA contact for Generali group companies --- extending automation from test tooling into business process automation.
\item Developed Java/J2EE application features for the PIA-Postkorb workflow portal; migrated WebServices to the XLDeploy process and contributed to an Apache Camel / Spring Boot dispatcher integration PoC.
\end{rSubsection}


\end{rSection}
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%	EDUCATION — FIXED
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\begin{rSection}{Education}
{M.Eng.\ Computer Aided Engineering (Software Design \& Engineering)} \hfill {\textcolor{black!60}{Oct 2010 -- Jul 2013}}\\
{Universit\"at der Bundeswehr M\"unchen}; thesis at Tongji University, Shanghai \hfill Thesis Grade: \textbf{1.0}\\
{\small Thesis: \textit{Development of a Web-Based Remote Fault Diagnosis System} (Neural Networks, PSO, Fuzzy Logic)}

{B.Eng.\ Information and Telecommunication Technologies} \hfill {\textcolor{black!60}{Oct 2007 -- Sep 2010}}\\
{Universit\"at der Bundeswehr M\"unchen}, Munich, Germany
\end{rSection}
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%	CERTIFICATIONS & AWARDS — FIXED
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\begin{rSection2}{Certifications \& Awards}
\item \textbf{IBM AI Engineering Specialization}, Coursera. Deep learning, TensorFlow, Keras, Apache Spark ML.
\item \textbf{AI for Trading Nanodegree}, Udacity / WorldQuant (2021). Quantitative ML, time-series analysis.
\item \textbf{AWS Certified Solutions Architect -- Associate}, Amazon Web Services (2024, active until Sep 2027).
\item \textbf{Data Engineering with AWS Nanodegree}, Udacity (2026). AWS data pipeline architecture.
\item \textbf{iSAQB CPSA -- Foundation Level}, iSAQB (2016). Certified Professional for Software Architecture.
\item \textbf{ITIL Foundation Certificate in IT Service Management}, PEOPLECERT / AXELOS (2016).
\end{rSection2}

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\textit{Languages: German (native), English (fluent)}
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\end{document}
