Nerijus Bertalis · Platform & Data Engineer
About me
I am a data and platform engineer based in Bern. My work covers the platform end to end: ingestion and modelling, CI/CD, and the monitoring that keeps it running.
My background is in cognitive systems, statistics and psychology with a focus on human factors (MSc Ulm, BSc Twente). It shapes how I work: I start from how people will use the data, and treat usability, clear definitions and trust as engineering requirements, not extras.
Experience
Data Engineer, isolutions, BernCurrent
Data and platform engineering for client projects.
- Platform and data engineering on a client’s Databricks platform, with Prometheus and Grafana observability and GitHub Actions automation.
- Fabric and Databricks projects: architecture, ETL/ELT with dbt, medallion layers, data marts and CI/CD.
- Fabric capacity monitoring and reporting, and a capacity utilisation strategy.
- Power BI solutions deployed through CI/CD.
Master's Thesis Intern, AI Data Platform, Volkswagen AG / CARIAD
Master's thesis: natural-language access to company data.
- Built a central data platform on Databricks, with ETL pipelines from several sources.
- Built text-to-SQL and natural-language data exploration features.
- Worked with stakeholders on requirements.
Data Architect & Analyst, TRUMPF GmbH
Cloud data solutions and reporting across departments.
- ETL pipelines with Databricks, Python and SQL, and Power BI dashboards for several departments.
- Databases on the Power Platform and support for the 1CRM data management platform.
- Azure data solutions together with cross-functional teams.
Education
MSc Cognitive Systems, University of Ulm, Germany
Statistics, machine learning, pattern recognition and programming, plus multidisciplinary AI and data analytics projects.
BSc Psychology, Statistics and Human Factors, University of Twente, Netherlands
Usability studies, statistical analysis and a foundation in Python and data tools.
Certifications
Skills
- Platforms
- Databricks, Microsoft Fabric, Azure, Power Platform
- Data engineering
- Python, SQL, Spark, dbt, NoSQL, ETL / ELT, Medallion architecture, Data modeling, Data warehousing
- Platform & DevOps
- GitHub Actions, CI/CD, Prometheus, Grafana, Observability, Fabric capacity monitoring, Scrum / DevOps
- BI & Analytics
- Power BI, Dashboards & reporting, Data marts, Statistics
- AI & Machine Learning
- Text-to-SQL, NLP, Natural-language data exploration, Pattern recognition
How I think about data platforms
Pick a platform and click a layer to see the tools and principles I apply.
Silver
Cleaned, deduplicated and conformed data.
- Enforce schema and data quality checks here.
- Model entities once so every consumer reuses them.