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Hi, I'm Aaron Venetz. A Data Systems Engineer — Spanning Cloud Infrastructure, Pipelines and Analytics.

My work lives at the intersection of data systems and software engineering. I build and operate cloud infrastructure, design data pipelines, and have the analytical depth to make sense of what flows through them. With a background spanning platform engineering, data engineering, statistical modelling and political science research, I bring a broad, multi-disciplinary perspective — equally comfortable working close to the infrastructure and working with the data itself.

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BA Social Sciences, University of Berne, Berne BE
Tutor "Introduction to Political Science", University of Berne, Berne BE
Undergraduate Research Assistant, University of Berne, Berne BE
MA Political Sciences, University of Berne, Berne BE
Politcal Scientist, gfs.bern, Berne BE
Cambridge English Level 3
Data Scientist, gfs.bern, Berne BE
Data Science, ZHAW, Winterthur ZH
Head of Data and Analytics, gfs.bern, Berne BE
Lead Data Platform Products / Data Engineer, PostAuto AG, Berne BE
BSC Computer Science, FFHS, Brig VS
AWS Certified Cloud Practitioner
Cloud Platform & Data Engineer, Die Schweizerische Post, Berne BE

My skillsMy skills

Cloud & Platform Engineering

My engineering approach centres on building reliable, secure and maintainable infrastructure. As a certified software architect and requirements engineer, I combine hands-on technical work with structured architectural thinking.

I specialise in AWS cloud infrastructure — designing IAM structures, managing Terraform-based environments, operating EC2 instances and building CI/CD pipelines with GitHub Actions. I manage Docker images for SageMaker and automation workflows, and have hands-on experience deploying and running Linux servers in production.

I also develop in Python (packages, APIs, frameworks) and R (Shiny, package development), and have experience with PySpark for large-scale data processing on AWS Glue.

AWS

Github

Linux

Docker

SQL

R

SPSS

Python

Data Science & Analytics

I have broad experience in data science, from raw data collection and cleaning through to statistical modelling, analysis and communication. At gfs.bern, I spent years building and refining quantitative models for Swiss national elections and referenda — including real-time vote projections broadcast on national television, where accuracy and speed under pressure were non-negotiable.

My analytical toolkit includes regression modelling, cluster analysis, principal component analysis, post-stratification, imputation methods and natural language processing. I have applied these techniques across national polling data, international surveys, media monitoring and text mining projects — always with a focus on methodological rigour and honest interpretation of results.

More recently, my data work has taken on a stronger engineering dimension: building ETL pipelines in PySpark and AWS Glue, managing data in Apache Iceberg format, and developing enterprise R Shiny dashboards and R packages used across PostAuto. My primary languages are R, Python and SQL, with additional experience in SPSS and Stata for academic-style analysis.

Political Science & Research

I have a strong background in political science, social research and quantitative data analysis, built up over years of academic study and applied research at gfs.bern, one of Switzerland’s leading political research institutes. My work there included designing and conducting national and international surveys, with a focus on crafting questions that genuinely capture what clients need to know — not just what is easy to ask.

I am experienced in a range of analysis methods suited to survey and social data: causal inference, multi-level modelling, longitudinal analysis and electoral behaviour modelling. My MA thesis focused on developing innovative methods for predicting Swiss election and referendum outcomes, and I co-authored a peer-reviewed publication on the validity of left-right political scales across European democracies.

My political science background gives me something that purely technical profiles often lack: the ability to contextualise data within its social and institutional setting, ask the right questions before building a model, and communicate findings clearly to non-technical audiences.

international surveys

forecasting

customer analysis

Projections

Decision Analysis

Contact MeContact me

Contact me here

Do you have a question, want to give feedback, or simply share something? I look forward to hearing from you! You can contact me by email or through the contact form on this page. Alternatively, you can connect with me directly via LinkedIn.

Location

: Aeschi b. Spiez, Berne, Switzerland

Languages

: German, English, French