Analytics Engineer

We are seeking a Data Engineer to support the ongoing development and operation of the Application, a central price adjustment calculation system in Customers sales domain. About the project: The Application is used for detailed monthly price adjustment calculations for existing electricity and gas customers in the retail portfolio. It supports key processes such as operational price adjustments, medium-term planning (MTP), scenario analysis, and both retrospective and prospective pricing calculations. To enable these processes, The Application integrates extensive business and technical data pipelines, validating and consolidating them into consistent baseline datasets used for decision-making – i.e. which tranche of contracts need to be adjusted at a given time. Additionally, the system provides critical metrics and analyses for reporting and control purposes, ensuring a high level of traceability of the pricing logic, portfolio effects, and how cost or volume changes impact results. Responsibilities: • Develop & Maintain Data Pipelines: Design, build, and maintain robust data pipelines (using SQL and DBT) to process and transform large volumes of data • Implement Requirements in Pipelines: Incorporate new business logic and regulatory requirements into the data pipeline workflows, ensuring compliance and correct calculations • Data Quality & Monitoring: Establish and enhance data quality checks, including implementing monitoring and alerting mechanisms to ensure pipeline outputs are accurate and reliable • Testing & Quality Assurance: Create and maintain comprehensive unit, integration, and regression tests for data pipelines to guarantee stability and facilitate safe changes • Data Modeling: Perform technical data modeling and design data model structures (ETL processes ingesting data from Data Warehouse / Snowflake) to support efficient data storage and retrieval • Pipeline Orchestration & Observability: Manage pipeline orchestration (e.g., using Apache Airflow) and ensure technical observability and data lineage tracking across the pipeline infrastructure • Performance & Reliability: Proactively optimize the performance of pipelines and ensure their robustness and reliability in production, including troubleshooting and resolving any technical issues Technologies: • SQL & Performance Tuning: Advanced SQL skills with hands-on experience in optimizing query performance on large datasets • DBT (Data Build Tool): Strong expertise in DBT, including writing tests, creating macros, and using version control for data transformations • Python Programming: Proficiency in Python for implementing complex data transformation logic and scripting tasks within the data pipeline • Data Warehousing & ETL: Solid knowledge of data warehousing concepts and ETL processes; experience with Snowflake or similar modern data platforms is highly desirable • Pipeline Tools: Familiarity with data pipeline orchestration and monitoring tools (e.g., Airflow, data observability frameworks) and best practices for maintaining data pipeline health Professional working proficiency in English is a must. German language skills (at least B2 level) are a plus. Start: 01.06.2026