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Octopus Energy's Energy Metering Germany GmbH is seeking a Mid-Level Data Engineer to build and operate a modern data and analytics infrastructure supporting Germany's energy transition. The role bridges robust data-lakehouse infrastructure, analytical reporting, and applied data-science use cases.
Key Responsibilities (50% Lakehouse & Data Engineering): Design, build, and optimize high-performance data pipelines using Databricks (Delta Lake, Unity Catalog). Implement data modeling with dbt and orchestrate robust DAGs via Apache Airflow. Establish automated data-quality checks, data lineage tracking, and cluster optimization.
(25% Analytics & Data Apps): Build semantic metric layers and self-service BI dashboards in Lightdash. Develop interactive analysis tools and data applications using Python and Streamlit.
(25% Data Science & ML): Conduct exploratory analyses, prototype, and train ML models (forecasting, anomaly detection). Manage experiment tracking on Databricks and deploy results for business stakeholders.
Required Experience: 2–4 years in Data Engineering, Analytics Engineering, or equivalent role. Deep hands-on expertise with Databricks, dbt, and Apache Airflow. Experience with Lightdash or code-based BI tools and Streamlit. Excellent SQL (performance tuning, complex joins) and strong Python (pandas, PySpark, scikit-learn). Proficiency with Git, CI/CD pipelines, and modern data modeling concepts (Star Schema). German language skills preferred.
The company is a regulated meter operator driving Germany's energy infrastructure modernization through digital, scalable, and practice-oriented solutions. You'll work on smart meter systems, wallbox solutions, and complex 1:n infrastructure management compliant with German energy regulations.
