Who We Are
Axpo is driven by a single purpose – to enable a sustainable future through innovative energy solutions. As Switzerland's largest producer of renewable energy and a leading international energy trader, Axpo leverages cutting-edge technologies to serve customers in over 30 countries. We thrive on collaboration, innovation, and a passion for driving impactful change.
About the Team
You will report directly to our Head of Development and join a team of highly committed IT data platform engineers with a shared goal: unlocking data and enabling self-service data analytics capabilities across Axpo. Our decentralized approach means close collaboration with various business hubs across Europe, ensuring local needs shape our global platform. You’ll find a mindset committed to innovation, collaboration, and excellence.
What You Will Do
As a Databricks Data Engineer, you will:
- Be a core contributor in Axpo’s data transformation journey by using Databricks as our primary data and analytics platform.
- Design, develop, and operate scalable data pipelines on Databricks, integrating data from a wide variety of sources (structured, semi-structured, unstructured).
- Leverage Apache Spark, Delta Lake, and Unity Catalog to ensure high-quality, secure, and reliable data operations.
- Apply best practices in CI/CD, DevOps, orchestration (e.g., Dragster, Airflow), and infrastructure-as-code (Terraform).
- Build re-usable frameworks and libraries to accelerate ingestion, transformation, and data serving across the business.
- Work closely with data scientists, analysts, and product teams to create performant and cost-efficient analytics solutions.
- Drive the adoption of Databricks Lakehouse architecture and help standardize data governance, access policies, and documentation.
- Ensure compliance with data privacy and protection standards (e.g., GDPR).
- Actively contribute to the continuous improvement of our platform in terms of scalability, performance, and usability.
What You Bring & Who You Are
We’re looking for someone with:
- A university degree in Computer Science, Data Engineering, Information Systems, or a related field.
- Strong experience with Databricks, Spark, Delta Lake, and SQL/Scala/Python.
- Proficiency in dbt, ideally with experience integrating it into Databricks workflows.
- Familiarity with Azure cloud services (Data Lake, Blob Storage, Synapse, etc.).
- Hands-on experience with Git-based workflows, CI/CD pipelines, and data orchestration tools like Dragster and Airflow.
- Deep understanding of data modeling, streaming & batch processing, and cost-efficient architecture.
- Ability to work with high-volume, heterogeneous data and APIs in production-grade environments.
- Knowledge of data governance frameworks, metadata management, and observability in modern data stacks.
- Strong interpersonal and communication skills, with a collaborative, solution-oriented mindset.
- Fluency in English.
Technologies You’ll Work With
- Core: Databricks, Spark, Delta Lake, Python, dbt, SQL
- Cloud: Microsoft Azure (Data Lake, Synapse, Storage)
- DevOps: Bitbucket/GitHub, Azure DevOps, CI/CD, Terraform
- Orchestration & Observability: Dragster, Airflow, Grafana, Datadog, New Relic
- Visualization: Power BI
- Other: Confluence, Docker, Linux
Nice to Have
- Experience with Unity Catalog and Databricks Governance Frameworks
- Exposure to Machine Learning workflows on Databricks (e.g., MLflow)
- Knowledge of Microsoft Fabric or Snowflake
- Experience with low-code analytics tools like Dataiku
- Familiarity with PostgreSQL or MongoDB
- Front-end development skills (e.g., for data product interfaces)
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