I build data pipelines, warehouses, and platforms that are rigorous by design — because I spent 15 years doing quantitative research before writing a single ETL job. Based in Salzburg, open to remote across the DACH region and beyond.
Design and implementation of robust data pipelines, harmonization of heterogeneous sources into unified data lakes and warehouses — with statistical taxonomies baked in from the start.
Standardization and taxonomic structuring of data at scale. From raw ingestion to analytics-ready models — built with reproducibility and long-term maintainability in mind.
Technical lead for frontend-to-database product delivery. Svelte frontends with a PostgreSQL backend, interactive Shiny dashboards, and HTML/CSS-based data applications. Working intensively with AI-assisted development tools (Cursor) since late 2025.
20+ years of quantitative methods, survey design, and multivariate modeling. I can tell you not just how to store the data, but what it actually means.
10+ years of self-hosted environments, containerized applications, and version-controlled workflows. Production-grade Linux administration including mail servers, web hosting, and Docker-based service stacks.
From exploratory analysis charts to production dashboards and interactive web apps. Communicating complex data to technical and non-technical stakeholders alike.
Technical lead for a full-stack software project delivering a Svelte/CSS/HTML frontend with a PostgreSQL backend. Architected and implemented a complete data pipeline for harmonizing and standardizing heterogeneous inputs into a data lake, with further processing into a data warehouse aligned to a statistical taxonomy.
Responsible for Austrian data collection across three survey waves and for harmonizing all country samples into an integrated international dataset in cooperation with AUSSDA and partner institutions across 18 countries. Built reproducible R pipelines for data processing and quality control. Dataset openly available for reuse.
Harmonized 18 independent national survey samples into a single integrated cross-national dataset in cooperation with AUSSDA. Designed and documented the integration schema for long-term reproducibility.
Statistical evaluation of large-scale recruitment experiments for Statistik Austria (Q2 and Q4/2016). Designed analysis pipelines in R, delivered reproducible reports and policy-facing documentation.
Production Shiny applications for dynamic data visualization and form-based data entry. Operates a personal self-hosted stack: git server, email, web, Docker-based services — all on managed Linux infrastructure.
Leading full-stack development and data architecture on a software project for the City of Salzburg. Responsible for frontend (Svelte), database (PostgreSQL), and data pipeline design including lake-to-warehouse processing. Since September 2025 working at sustained high output with AI-assisted development in Cursor — shipping code daily across the full stack.
Quantitative social research, survey data infrastructure, and international data harmonization. Led the Values in Crisis Austria study (3 survey waves, open dataset). Member of the AUSSDA User Advisory Board; co-editor, Österreichische Zeitschrift für Soziologie.
Data acquisition, pipeline development, and analysis within the Digitize! research project. Produced an Open Educational Resource (OER) on data methods.
12 years of applied quantitative research and teaching across three institutions — building data pipelines, analytical models, and study infrastructure from scratch long before it was called "data engineering."
Key projects during this period:
Independent consulting for research design, data collection, and statistical analysis for medical, social, and public-sector clients. Delivered reproducible R-based pipelines and policy-facing reports.
Selected mandates:
Supported the Committee on Employment and Social Affairs, combining policy analysis with international stakeholder coordination.
I am a data engineer with an unusual origin story: I spent 15 years as a quantitative social scientist before moving into engineering roles. That background means I care deeply about what data represents — not just how it flows.
My engineering skills grew organically from research necessity: when you need reproducible pipelines, harmonized cross-national datasets, and interactive dashboards for non-technical stakeholders, you build them yourself. Over time, Docker, PostgreSQL, Svelte, and Linux server administration became core tools, not sidelines.
I hold a PhD (Dr. phil.) from Paris Lodron Universität Salzburg and an MSc from KU Leuven. I teach at the Paracelsus Medical University, where I was voted Teacher of the Year in 2020. I speak German (native) and English (professional).
I am based in Salzburg, Austria and open to roles across the DACH region, fully remote, or internationally remote.
I am actively looking for Data Engineering roles — full-time or freelance — in Salzburg, remote across Austria, or internationally remote. If you are building data infrastructure and need someone who understands the data as deeply as the pipeline, let's have a conversation.