Basel, Switzerland · Full time · Permanent · On-site, with time at client sites
For engineers who make data trustworthy, and make it move.
At ekona , we build production-grade AI systems and applications for clients in life sciences , supply chain , consumer goods and finance . Every planning tool, forecasting engine and AI agent we ship depends on data that has to be right. That data starts as messy master data, ERP extracts, product hierarchies and documents. We turn it into models people trust and decisions they can defend.
We're looking for data engineers who own that foundation end to end. You don't wait for a perfect spec of the source systems. You dig into the data, find what's broken, fix it, and make sure it stays fixed. And you can sit with a client's data team and their domain experts and speak both languages.
If that sounds like you, keep reading.
What You'll Do
Build pipelines that hold up. Design and run ELT pipelines with dbt and Airflow on Snowflake and other cloud data platforms. Model data into clean, documented, tested marts that applications and AI agents can rely on.
Make data trustworthy. Profile and reconcile data across sources and environments. Build data-quality checks into the pipeline, so problems surface before a planner or an agent sees them.
Work with real enterprise sources. ERP and PLM systems such as SAP, master data, product hierarchies and bills of materials, plus the spreadsheets and documents nobody planned for.
Feed applications and AI. Work alongside our AI and software engineers so data lands where it is needed: planning and simulation tools, forecasting models, knowledge graphs and retrieval systems.
Ship like a software engineer. Version control, code review, CI/CD, infrastructure as code, and changes promoted properly from dev to production.
Shape how we work. Help build our data engineering playbook, templates and tooling. Your ideas will be heard.
What We're Looking For
How you think about data matters more than any single tool. You'll likely be a fit if you have:
- Several years of professional data engineering experience , with pipelines running in production
- Strong SQL and Python
- Hands-on experience with dbt, Airflow and Snowflake , or close equivalents such as Dagster, Prefect, Databricks or BigQuery
- Solid data modeling , and the judgment to keep models simple
- Good engineering habits : at least one major cloud platform (GCP, Azure or AWS), Git workflows, CI/CD and containers. Terraform is a plus
- A data-quality mindset : testing, reconciliation and lineage are part of the job, not an afterthought
- The ability to talk to non-technical stakeholders and turn their questions into data that answers them
- Very good English , spoken and written. German is a plus
Nice to have: SAP data (S/4HANA, material master, BOM, PLM); Databricks; graph databases such as Neo4j; data for ML and LLM applications (feature pipelines, embeddings, RAG); experience in consumer goods, life sciences, supply chain or finance; regulated environments.
Why ekona
- Your data powers things people use. Planning tools, forecasting engines and AI agents in production, not reports nobody opens.
- Engineering quality actually matters. Our clients feel the difference, and so will you.
- Real projects, regulated industries. The work has weight.
- Small team, high bar. Autonomy, trust and direct influence on where we go next.
- No AI theater. No bureaucracy, no endless meetings, no demos dressed up as deliverables.
Is This You?
If you would rather receive a perfectly specified ticket and never meet the people who use the data, this probably isn't the right place.
If you like getting to the bottom of messy data and building pipelines that make it trustworthy, it probably is.
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