Background

What I have been responsible for, and what trained me for it

The overview page says what I do. This page says what that has meant in practice: the responsibilities I have carried across data, delivery and platform work, the studies behind them and the courses taken since. Grouped by theme rather than by station, because the themes are what carry over.

Responsibilities

Application modernisation

Bringing legacy systems into the present without stopping the business that runs on them.

  • Designed and built web frontends in TypeScript and React, on Bun, to replace ageing interfaces.
  • Containerised legacy and greenfield applications with Docker and deployed them to Kubernetes through custom Helm charts.
  • Designed SQL schemas and ETL pipelines that move complex datasets from legacy structures to current standards without loss.

Delivery automation

Pipelines that build, test and ship, so that a release stops being an event.

  • Engineered GitLab CI pipelines and Bash tooling that build, archive and deploy artifacts, cutting manual release work.
  • Standardised local and CI environments with Docker Compose so that development matched production.
  • Established quality gates with SonarQube static analysis and Playwright end-to-end tests.

Traffic & developer tooling

The layer between the network and the code, and the tools that make it visible.

  • Configured Nginx and Traefik for reverse proxying and dynamic service discovery.
  • Built Python (Flask) API wrappers around command-line monitoring tools, giving developers a web view of application health.
  • Run the same patterns privately: a GitOps-managed Kubernetes platform with full observability and layered security.

Data warehousing & pipelines

One source of truth built from scratch, and the pipelines that keep it filled.

  • Architected a unified data warehouse from the ground up, with a schema built for aggregation and anonymisation, as the central source for analysts.
  • Developed Python and SQL pipelines for ingestion and for large-scale external extracts over SFTP.
  • Optimised high-load SQL databases and wrote migration scripts that brought unstructured product data into existing patterns.
  • Built pipelines for parsing, normalising and standardising address data, and matched messy address stocks against geographic hierarchies and coordinates.

Data quality & reporting

Knowing the data is right before anyone builds on it, and showing what it says.

  • Implemented statistical monitoring and threshold-based alerting in R and Python to catch ingestion errors and product incidents before they reached a report.
  • Delivered performance insights through custom dashboards (SSRS, Python) and ad-hoc visualisations.
  • Served as the first contact for external stakeholders, turning requirement analysis into data deliveries.

Requirements & stakeholders

Translating between the people who need software and the people who build it.

  • Acted as technical mediator for end users, translating qualitative requirements into precise technical specifications.
  • Defined data specifications with product owners and finalised feature scopes.
  • Worked as the established interface between business units and engineering.

Security hardening & standards

Making the secure configuration the default one, across teams.

  • Co-authored guidelines for Docker deployments, security hardening and standardised server configuration with colleagues from other units.
  • Moved container workloads from rootful to rootless Docker, with SELinux integration and standardised UID/GID namespace mapping.
  • Wired a central artifact repository for container images into the build and deploy pipelines.

Knowledge sharing & mentoring

Documentation that outlives the meeting, and colleagues who can take a stack over.

  • Contributed a React and TypeScript frontend as an internal reference stack, with architecture, tooling, design decisions and operations documented in writing.
  • Kept GitLab wikis, Markdown architecture notes and structured issue threads as the shared record of decisions.
  • Mentored interns and a junior engineer through onboarding and day-to-day code work.

Studies

M.A. Digital Humanities

Focus on NLP and data science · University of Vienna

The thesis built a full NLP pipeline, from tokenisation and embeddings to LDA topic modelling and network analysis, over a corpus of gothic fiction. Alongside it: a legacy text-analysis toolset refactored from Perl to Python, and a weakly supervised NER model for medical text built with PyTorch and Knodle. Performance scholarship; degree with distinction.

B.A. Comparative Literature

Applied literary studies · University of Vienna

Close reading before distant reading. The training in how texts are built is what later made the computational work on them worth doing. Performance scholarship.

Certificates & courses

Engineering

  • Decoding DevOps

    Infrastructure automation, Jenkins, Argo CD, Kubernetes and monitoring.

    Udemy

  • The Complete Full-Stack Web Development Bootcamp

    Modern web architecture with React, Express, Node.js and database integration.

    Udemy

  • Object Oriented Programming in Python

    Classes, inheritance and design principles for object oriented Python.

    Boot.dev

  • Backend Developer Path, TypeScript and Python

    Course path on HTTP servers, SQL, algorithms and distributed systems.

    Boot.dev In progress

  • DevOps Engineer Path, Go and Python

    Course path on Linux, Docker, Kubernetes, CI/CD and cloud deployment.

    Boot.dev In progress

Methods

  • Klare Anforderungen für kleinere IT-Projekte entwickeln

    Seminar on requirements engineering for smaller IT projects in public administration.

    Verwaltungsakademie des Bundes

Data & analytics

  • IBM Data Science Professional Certificate

    A nine-course specialisation covering data analysis, visualisation and methodology.

    Coursera

  • IBM Data Analyst Professional Certificate

    Data analysis with SQL, Python and dashboarding tools.

    Coursera

  • IBM Data Analysis & Visualization Foundations

    Specialisation on the foundations of data analysis and visualisation.

    Coursera

  • Business Metrics for Data-Driven Companies

    Which metrics matter, and how to read them.

    Duke University · Coursera

  • Data Visualization and Communication with Tableau

    Visual analysis and presenting findings in Tableau.

    Duke University · Coursera

  • Power BI Fundamentals

    Reports and data models in Power BI.

    Udemy

  • KNIME Analytics Platform

    Basic and advanced proficiency in visual data workflows.

    KNIME

Research & language

  • Data or Specimens Only Research

    Research ethics for work with human data.

    CITI Program

  • Certificate in Advanced English (C1)

    Cambridge ESOL, Level 2.

    University of Cambridge

Community

Regular at the DevOps, Platform Engineering and Data Engineering meetups in Vienna, including their full-day formats, and at the Women in Data Science conference in Villach.

Selected resources

A selection of the technical literature and podcasts I can recommend.

Podcasts

  • Book OverflowTwo engineers read a software book a week and talk it through.
  • The Pragmatic Engineer PodcastGergely Orosz in conversation with people who build and run software at scale.
  • c't 4004The c't 3003 crew on this week's tech, in German, every Thursday.

Data analysis & statistics

  • Exploratory Data AnalysisJohn W. Tukey · 1977
  • Hands-On Exploratory Data Analysis with PythonSuresh Kumar Mukhiya · 2020
  • Practical Statistics for Data ScientistsPeter Bruce, Andrew Bruce, Peter Gedeck · 2020
  • Doing Data ScienceRachel Schutt, Cathy O'Neil · 2013
  • Data Science for BusinessFoster Provost, Tom Fawcett · 2013
  • Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlowAurélien Géron · 2019

Data engineering & databases

  • Fundamentals of Data EngineeringJoe Reis, Matt Housley · 2022
  • Data Pipelines Pocket ReferenceJames Densmore · 2021
  • The Data Warehouse ToolkitRalph Kimball, Margy Ross · 2013
  • SQL CookbookAnthony Molinaro, Robert de Graaf · 2020
  • T-SQL QueryingItzik Ben-Gan, Adam Machanic, Dejan Sarka, Kevin Farlee · 2015

DevOps & platform

  • Das DevOps-HandbuchGene Kim, Jez Humble, Patrick Debois, John Willis · 2022
  • DevOps for the DesperateBradley Smith · 2022
  • Python for DevOpsNoah Gift, Kennedy Behrman, Alfredo Deza, Grig Gheorghiu · 2019
  • Docker: Up & RunningSean P. Kane, Karl Matthias · 2023
  • Kubernetes Best PracticesBrendan Burns, Eddie Villalba, Dave Strebel, Lachlan Evenson · 2023

JavaScript & TypeScript

  • Eloquent JavaScriptMarijn Haverbeke · 2024
  • Data Structures and Algorithms in JavaScriptFederico Kereki · 2025
  • Programming TypeScriptBoris Cherny · 2019
  • Node.js: The Comprehensive GuideSebastian Springer · 2025
  • React and React NativeMikhail Sakhniuk, Adam Boduch · 2024
  • Fullstack-EntwicklungPhilip Ackermann · 2023

Python

  • Fluent PythonLuciano Ramalho · 2022
  • Django in ProductionArghya Saha · 2024
  • Ultimate Django for Web App Development Using PythonLeonardo Luis Lazzaro · 2024

Linux, networking & security

  • How Linux WorksBrian Ward · 2014
  • Automating Linux and Unix System AdministrationNate Campi, Kirk Bauer · 2008
  • Classic Shell ScriptingArnold Robbins, Nelson H. F. Beebe · 2005
  • Linux Basics for HackersOccupyTheWeb · 2018
  • The Practice of Network Security MonitoringRichard Bejtlich · 2013

Software craft & architecture

  • Fundamentals of Software ArchitectureMark Richards, Neal Ford · 2025
  • Think Like a ProgrammerV. Anton Spraul · 2012
  • Learning GitAnna Skoulikari · 2023