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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 $\vert$ Zurich on-site / hybrid}
\address{{Senior Software Engineer $\vert$ Backend Data Platform $\cdot$ Observability $\cdot$ Reliability $\vert$ Python $\cdot$ Java $\cdot$ AWS}}


\begin{document}

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%	SUMMARY
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\begin{rSection}{Summary}
Software engineer with 11+ years building and owning production data and telemetry pipelines end-to-end. I own the Fulfillment and Product Analysis data pipelines at Switzerland's largest telco (Oracle and \textbf{Kafka} ingestion, Teradata, \textbf{AWS} S3/Glue/Athena with \textbf{Apache Iceberg}, \textbf{Airflow}) under on-call SLA, and earlier built observability and anomaly-detection tooling (\textbf{ELK}, Kafka, \textbf{Grafana}, \textbf{Prometheus}, Loki) for a 24/7 Bosch fab. I work across distributed backend systems with \textbf{Python} and \textbf{PySpark}, ship services on Kubernetes, and carry root-cause analysis under SLA. Python expert and polyglot (Java, C++); AWS Solutions Architect; currently learning \textbf{Go}.
\end{rSection}
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%	TECHNICAL SKILLS — Format C, 5 groups (4-3-2-2-2)
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\begin{rSection}{Technical Skills}

\begin{skillgroup}{Data Platform, Observability \& Distributed Systems}
\skilldash{\textbf{Kafka}, \textbf{Airflow}, \textbf{PySpark} / Apache Spark, \textbf{Apache Iceberg}, Parquet, Hadoop / ImpalaSQL, ETL/ELT pipeline design, data lakehouse}
\skilldash{Observability \& telemetry: \textbf{ELK Stack} (Elasticsearch / Logstash / Kibana), \textbf{Grafana}, \textbf{Prometheus}, Loki, monitoring, alerting}
\skilldash{High-throughput ingestion, batch and stream processing, distributed systems, columnar storage, backfills, schema evolution}
\skilldash{\textbf{SQL} (Oracle $\cdot$ Teradata $\cdot$ Impala $\cdot$ Postgres), query optimization, data modeling, partitioning, data lineage}
\end{skillgroup}

\begin{skillgroup}{Cloud-Native Infrastructure \& Reliability}
\skilldash{\textbf{AWS} (S3, Glue, Athena/Iceberg, \textbf{Redshift}, Lambda, Step Functions, \textbf{Airflow}, CloudFormation); GCP (transferable)}
\skilldash{\textbf{Kubernetes}, \textbf{Docker}, Ansible, GitLab CI/CD, Jenkins, Infrastructure as Code, serverless}
\skilldash{SLOs, SRE practices, SLA / on-call ownership, incident response, root-cause analysis, pipeline reliability}
\end{skillgroup}

\begin{skillgroup}{Programming Languages \& APIs}
\skilldash{\textbf{Python} (expert), \textbf{Java} (strong), SQL, C++ (Vizrt, legacy), C\#, JavaScript / TypeScript, Bash; \textbf{Go} (learning)}
\skilldash{REST APIs, FastAPI / Flask, Express.js, OpenAPI, data structures \& algorithms, software design patterns}
\end{skillgroup}

\begin{skillgroup}{Data Mesh, Governance \& AI-Assisted}
\skilldash{Data Mesh, data products, metadata, data catalog, data governance, data quality, data validation}
\skilldash{ML inference deployment / MLOps; AI-assisted development (Copilot, LiteLLM, custom GPTs, Kiro)}
\end{skillgroup}

\begin{skillgroup}{Certifications}
\skilldash{\textbf{AWS Certified Solutions Architect -- Associate} (active until Sep 2027), Data Engineering with AWS (Udacity)}
\skilldash{iSAQB CPSA -- Foundation Level (software architecture), ITIL Foundation; IBM AI Engineering Specialization}
\end{skillgroup}

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

% --- Swisscom (Oct 2023 -- Present) — 6 bullets: SW-2, SW-1, SW-7, SW-3, SW-6, SW-4 ---
\begin{rSubsection}{Backend Data Platform, Lakehouse \& Pipeline Reliability}{\textcolor{black!60}{Oct 2023 -- Present}}{Staff Data, Analytics \& AI Engineer, Swisscom (Schweiz) AG}{Bern, Switzerland}
\item Owned Fulfillment and Product Analysis data pipelines end-to-end (Oracle, \textbf{Kafka} to Teradata in \textbf{Python}) as Component Owner, carrying on-call SLA, root-cause analysis and governance for telecom-scale flows.
\item Migrated my domains' Teradata/Oracle ETL stack to a cloud-native \textbf{AWS} lakehouse (S3, Glue, Athena with \textbf{Apache Iceberg}, \textbf{Redshift}, \textbf{Airflow}, CloudFormation), moving batch ETL off Teradata onto serverless S3 and Glue.
\item Modeled governed data products with metadata and lineage within Swisscom's company-wide Data Mesh on \textbf{AWS} (Glue, Athena, CI/CD), the data foundation that downstream analytics and AI/agentic workflows query.
\item Designed, deployed and operate \textbf{Python} backend data services and APIs on \textbf{Kubernetes} with GitLab CI/CD, owning containerized delivery from build and test through production rollout under on-call duty.
\item Built distributed data processing with \textbf{PySpark} across the Swisscom Data Lake, scaling \textbf{Python} and \textbf{SQL} pipelines to high-throughput batch workloads over large Fulfillment and Product Analysis datasets.
\item Delivered data products for B2B stakeholders and drove \textbf{Python} automation plus 3rd-level root-cause analysis under on-call SLA, keeping large-scale pipelines reliable and observable for downstream consumers.
\end{rSubsection}

% --- Bosch (Feb 2020 -- Dec 2022) — 4 bullets: BS-4 (LEAD, observability), BS-2, BS-1, BS-3 ---
\begin{rSubsection}{Observability, Telemetry Pipelines \& Production Data Services}{\textcolor{black!60}{Feb 2020 -- Dec 2022}}{(Senior) Data Engineer, Robert Bosch Semiconductor Manufacturing}{Dresden, Germany}
\item Built an observability and anomaly-detection proof of concept (\textbf{ELK} with \textbf{Kafka}, \textbf{Grafana}, \textbf{Prometheus}, Loki) for 24/7 semiconductor production, centralizing log and metric ingestion with dashboards and alerting.
\item Developed data services in \textbf{Python}, \textbf{Java} and C\# over OracleDB and Hadoop/ImpalaSQL, optimizing query performance over large columnar datasets for semiconductor defect-management and process-optimization teams.
\item Containerized and orchestrated \textbf{ML inference} (\textbf{Docker}, \textbf{Kubernetes}, Ansible) into Bosch's 24/7 fab, automating image-based defect classification across 300mm wafer lines with no production downtime.
\item Served as Application Owner for the semiconductor analytics suite and upstream pipelines, defining SLOs, managing vendors, and delivering code review, training and docs across cross-functional fab operations teams.
\end{rSubsection}

% --- Fraunhofer (Sep 2018 -- Oct 2019) — 3 bullets: FC-3, FC-1, FC-2 ---
\begin{rSubsection}{Distributed Services \& Applied ML Engineering}{\textcolor{black!60}{Sep 2018 -- Oct 2019}}{Research Software Engineer, Fraunhofer-Center for Maritime Logistics CML}{Hamburg, Germany}
\item Built microservices and \textbf{REST APIs} (Express.js, \textbf{Docker}, SQLite) for MISSION, a Fraunhofer maritime data-exchange platform, enabling structured data interchange across ports, operators and research partners.
\item Independently set up the team's first Jenkins CI/CD pipeline with quality gates and build automation, and developed the SCEDAS crew-scheduling system (C\#, .NET, MS SQL Server, Entity Framework).
\item Contributed \textbf{ML} and NLP components to ARTUS, a Fraunhofer research project for automatic sea-rescue speech transcription, applying speech recognition and machine learning in a safety-critical maritime domain.
\end{rSubsection}

% --- Vizrt (Jul 2017 -- May 2018) — 2 bullets: VZ-1, VZ-2 ---
\begin{rSubsection}{Distributed Real-Time Backend at Broadcast Scale}{\textcolor{black!60}{Jul 2017 -- May 2018}}{DevOps Engineer, Vizrt}{Bergen, Norway}
\item Engineered \textbf{distributed} real-time video transcoding backend components in \textbf{Python} (with legacy C++ modules) for Vizrt's broadcast platform, serving global media customers including CNN, BBC and Al Jazeera.
\item Built an automated integration and unit test suite for A/V streaming in \textbf{Python} and integrated quality gates into the CI/CD pipeline, which shortened the feedback loop and raised release quality.
\end{rSubsection}

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


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%	EDUCATION — FIXED (KB-corrected dates)
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\begin{rSection}{Education}
{M.Eng.\ Computer Aided Engineering (Software Design \& Engineering)} \hfill {\textcolor{black!60}{Apr 2012 -- Oct 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 2009 -- Oct 2012}}\\
{Universit\"at der Bundeswehr M\"unchen}, Munich, Germany
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%	CERTIFICATIONS & AWARDS — FIXED
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\begin{rSection2}{Certifications \& Awards}
\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).
\item \textbf{IBM AI Engineering Specialization}, Coursera. Deep learning, TensorFlow, Keras, Apache Spark ML.
\end{rSection2}

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