b4b5e3fbe1
Finalized package retained for reuse; role closed (Cisco scrape 2026-06-02: not on board, Recruitee link dead). PDFs/build artifacts gitignored. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
165 lines
12 KiB
TeX
165 lines
12 KiB
TeX
\documentclass{resume}
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\usepackage{hyperref}
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\usepackage{enumitem}
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\usepackage{fontawesome}
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\usepackage{tikz}
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\usepackage{xcolor}
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\usepackage[T1]{fontenc}
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\usepackage{lmodern}
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\usepackage[version=4,arrows=pgf-filled]{mhchem}
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\usepackage[includefoot,left=0.5in,top=0.5in,right=0.5in,bottom=0.2in,textwidth=7.5in,textheight=10.8in]{geometry}
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\fancyfoot[R]{\hfill \thepage/\pageref{LastPage}}
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\newcommand{\tab}[1]{\hspace{.2667\textwidth}\rlap{#1}}
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%----------------------------------------------------------------------------------------
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% HEADER
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%----------------------------------------------------------------------------------------
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\name{Dennis Thiessen, M.Eng.}
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\address{\href{https://linkedin.com/in/dennis-thiessen}{LinkedIn}}
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\address{dennis@thiessen.io \\ +41 795 955 585}
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\address{Bern, Switzerland $\vert$ German citizen $\vert$ Available remote across DACH/EU/UK}
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\address{{Senior Data Engineer $\vert$ Pipelines $\cdot$ Columnar Analytics $\cdot$ Observability $\vert$ Kubernetes $\cdot$ AWS $\cdot$ Python}}
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\begin{document}
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\vspace{-0.15cm}
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%----------------------------------------------------------------------------------------
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% SUMMARY
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%----------------------------------------------------------------------------------------
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\begin{rSection}{Summary}
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Data engineer with 11+ years building production data platforms and pipelines at scale. I build and own cloud-native data pipelines and products on Switzerland's largest telco's \textbf{AWS} platform (\textbf{Kafka}, \textbf{Airflow}, \textbf{Redshift}, PySpark, \textbf{Kubernetes}, GitLab CI/CD), with deep \textbf{SQL} and query optimization across Teradata, Redshift and Impala columnar stores. Built and operated full \textbf{observability} stacks (\textbf{Grafana}, \textbf{Prometheus}, Loki, ELK) for a 24/7 Bosch semiconductor fab, and engineered distributed real-time backends at Vizrt for CNN, BBC and Al Jazeera. \textbf{Python} expert and polyglot (Java, C++); AWS Solutions Architect; currently learning \textbf{Go}.
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\end{rSection}
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\vspace{-0.15cm}
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%----------------------------------------------------------------------------------------
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% TECHNICAL SKILLS — Format C, 5 groups (4-3-2-2-2)
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%----------------------------------------------------------------------------------------
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\begin{rSection}{Technical Skills}
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\begin{skillgroup}{Data Engineering \& Distributed Systems}
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\skilldash{\textbf{Kafka}, \textbf{Airflow}, \textbf{PySpark} / Apache Spark, Apache Iceberg, Hadoop / ImpalaSQL, ETL/ELT pipeline design}
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\skilldash{\textbf{SQL} (Oracle $\cdot$ Teradata $\cdot$ Impala $\cdot$ Postgres), query optimization, data modeling, partitioning, indexing}
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\skilldash{High-throughput ingestion pipelines, batch and stream processing, distributed systems, data lakehouse}
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\skilldash{Data Mesh, data products, metadata management, data catalog, data governance, SLA / on-call ownership}
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\end{skillgroup}
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\begin{skillgroup}{Cloud-Native Infrastructure \& Observability}
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\skilldash{\textbf{Kubernetes}, \textbf{Docker}, Ansible, GitLab CI/CD, Jenkins, Infrastructure as Code, serverless, DevSecOps}
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\skilldash{\textbf{AWS} (S3, Glue, Athena/Iceberg, \textbf{Redshift}, Lambda, Step Functions, \textbf{Airflow}, CloudFormation)}
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\skilldash{\textbf{Grafana}, \textbf{Prometheus}, Loki, ELK Stack (Elasticsearch, Logstash, Kibana), monitoring, alerting, telemetry}
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\end{skillgroup}
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\begin{skillgroup}{Columnar \& Analytical Databases}
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\skilldash{\textbf{Teradata}, \textbf{Redshift}, Hadoop / Impala (MPP / columnar OLAP), OracleDB, large-dataset query tuning}
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\skilldash{ClickHouse-class columnar analytics (transferable from Teradata / Redshift / Impala), data warehouse modeling}
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\end{skillgroup}
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\begin{skillgroup}{Programming Languages \& APIs}
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\skilldash{\textbf{Python} (expert), \textbf{Java} (strong), SQL, JavaScript / TypeScript, Bash; \textbf{Go} (learning)}
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\skilldash{REST APIs, FastAPI / Flask, Express.js, OpenAPI; C++ (Vizrt, legacy), C\# / .NET (Bosch / Fraunhofer, legacy)}
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\end{skillgroup}
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\begin{skillgroup}{Certifications}
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\skilldash{\textbf{AWS Certified Solutions Architect -- Associate} (active until Sep 2027), Data Engineering with AWS (Udacity)}
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\skilldash{iSAQB CPSA -- Foundation Level (software architecture), ITIL Foundation; Security Champion (DevSecOps, 2025/26)}
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\end{skillgroup}
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\end{rSection}
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\vspace{-0.15cm}
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%----------------------------------------------------------------------------------------
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% PROFESSIONAL EXPERIENCE
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%----------------------------------------------------------------------------------------
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\begin{rSection}{Professional Experience}
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% --- Swisscom (Oct 2023 -- Present) — 6 bullets: SW-2, SW-1, SW-7, SW-3, SW-6, SW-4 ---
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\begin{rSubsection}{Cloud-Native Data Platform, Pipelines \& Observability at Telecom Scale}{\textcolor{black!60}{Oct 2023 -- Present}}{Staff Data, Analytics \& AI Engineer, Swisscom (Schweiz) AG}{Bern, Switzerland}
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\item Owned Fulfillment and Product Analysis ETL pipelines (Oracle, \textbf{Kafka} to Teradata in \textbf{Python}) as Component Owner, enforcing data governance and SLA compliance for business-critical, telecom-scale data flows.
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\item Migrated the legacy Teradata/Oracle ETL stack to cloud-native \textbf{AWS} (S3, Glue, \textbf{Airflow}, Athena/Iceberg, \textbf{Redshift}, CloudFormation IaC), enabling scalable serverless processing for analytics and ML workloads.
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\item Built governed data products and metadata management within Swisscom's company-wide Data Mesh on \textbf{AWS} (Glue, Athena, CloudFormation, CI/CD), making them discoverable for downstream teams to query directly.
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\item Designed, deployed and operate \textbf{Python} data services on \textbf{Kubernetes} with GitLab CI/CD automation, owning containerized delivery from build and test through production rollout in an agile DevOps team.
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\item Applied \textbf{PySpark} and distributed computing across the Swisscom Data Lake to process large-scale datasets, extending \textbf{Python} and \textbf{SQL} pipelines to high-volume batch workloads for Fulfillment and Product Analysis.
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\item Delivered data products, analyses and dashboards for B2B stakeholders, and drove \textbf{Python} automation of recurring workflows plus 3rd-level root cause analysis under on-call duty to keep the platform reliable.
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\item Hold the team's Security Champion role (2025/26), owning DevSecOps compliance, risk monitoring and deviation tracking for the data platform, with 100h of annual cloud-security and security-by-design training.
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\end{rSubsection}
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% --- Bosch (Feb 2020 -- Dec 2022) — 4 bullets: BS-4, BS-2, BS-1, BS-3 ---
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\begin{rSubsection}{Observability, Production ML \& Data Services in 24/7 Semiconductor Manufacturing}{\textcolor{black!60}{Feb 2020 -- Dec 2022}}{(Senior) Data Engineer, Robert Bosch Semiconductor Manufacturing}{Dresden, Germany}
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\item Designed and ran a centralized \textbf{observability} stack (ELK with \textbf{Kafka} ingestion, \textbf{Grafana} dashboards, \textbf{Prometheus} metrics, Loki logs) for anomaly detection and monitoring across 24/7 semiconductor production.
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\item Built data services in \textbf{Python}, Java and C\# over OracleDB and Hadoop/ImpalaSQL, optimizing query performance over large analytics datasets for semiconductor defect-management and process-optimization teams.
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\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.
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\item Served as Application Owner for the semiconductor analytics suite and upstream pipelines, defining SLOs, managing vendors, and delivering training and docs across cross-functional fab operations teams.
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\end{rSubsection}
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% --- Fraunhofer (Sep 2018 -- Oct 2019) — 3 bullets: FC-3, FC-1, FC-2 ---
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\begin{rSubsection}{Microservice Engineering \& Applied Data Research}{\textcolor{black!60}{Sep 2018 -- Oct 2019}}{Research Software Engineer, Fraunhofer-Center for Maritime Logistics CML}{Hamburg, Germany}
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\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.
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\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).
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\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.
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\end{rSubsection}
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% --- Vizrt (Jul 2017 -- May 2018) — 2 bullets: VZ-1, VZ-2 ---
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\begin{rSubsection}{Distributed Real-Time Backend Engineering at Broadcast Scale}{\textcolor{black!60}{Jul 2017 -- May 2018}}{DevOps Engineer, Vizrt}{Bergen, Norway}
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\item Engineered 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.
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\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.
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\end{rSubsection}
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% --- Generali (May 2015 -- Jun 2017) — 2 bullets: GN-1, GN-3 ---
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\begin{rSubsection}{Test Automation, CI/CD \& Java Backend}{\textcolor{black!60}{May 2015 -- Jun 2017}}{IT Consultant, Generali Deutschland Informatik Services}{Hamburg, Germany}
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\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.
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\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.
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\item Developed 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.
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\end{rSubsection}
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\end{rSection}
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\vspace{-0.15cm}
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%----------------------------------------------------------------------------------------
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% EDUCATION — FIXED (dates per KB correction: B.Eng Oct 2009--Oct 2012, M.Eng Apr 2012--Oct 2013)
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%----------------------------------------------------------------------------------------
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\begin{rSection}{Education}
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{M.Eng.\ Computer Aided Engineering (Software Design \& Engineering)} \hfill {\textcolor{black!60}{Apr 2012 -- Oct 2013}}\\
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{Universit\"at der Bundeswehr M\"unchen}; thesis at Tongji University, Shanghai \hfill Thesis Grade: \textbf{1.0}\\
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{\small Thesis: \textit{Development of a Web-Based Remote Fault Diagnosis System} (Neural Networks, PSO, Fuzzy Logic)}
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{B.Eng.\ Information and Telecommunication Technologies} \hfill {\textcolor{black!60}{Oct 2009 -- Oct 2012}}\\
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{Universit\"at der Bundeswehr M\"unchen}, Munich, Germany
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\end{rSection}
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\vspace{-0.15cm}
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%----------------------------------------------------------------------------------------
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% CERTIFICATIONS & AWARDS — FIXED
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%----------------------------------------------------------------------------------------
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\begin{rSection2}{Certifications \& Awards}
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\item \textbf{AWS Certified Solutions Architect -- Associate}, Amazon Web Services (2024, active until Sep 2027).
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\item \textbf{Data Engineering with AWS Nanodegree}, Udacity (2026). AWS data pipeline architecture.
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\item \textbf{iSAQB CPSA -- Foundation Level}, iSAQB (2016). Certified Professional for Software Architecture.
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\item \textbf{ITIL Foundation Certificate in IT Service Management}, PEOPLECERT / AXELOS (2016).
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\item \textbf{IBM AI Engineering Specialization}, Coursera. Deep learning, TensorFlow, Keras, Apache Spark ML.
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\end{rSection2}
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\begin{center}
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\vspace{0.1cm}
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\textit{Languages: German (native), English (fluent)}
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\end{center}
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\end{document}
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