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Data Engineer | Snowflake / Databricks / dbt / Airflow | Data Warehouse & Data Modelling
Posted 1 week ago
Main tasks & responsibilities
- Design, develop and maintain scalable, efficient and reliable data models and pipelines as part of an agile data engineering team.
- Collaborate with data analysts and business stakeholders to understand business requirements and translate them into scalable data solutions.
- Redesign and rebuild foundational data models across the Data Vault and presentation layers to accommodate changes in the underlying Billing and CRM source systems.
- Design and implement business-specific data products to support different business areas, including Tax, Sales and Billing.
- Support the migration of the data platform from Snowflake to Databricks, while maintaining and further developing the existing data architecture.
- Optimize existing data pipelines to improve performance, cost efficiency and maintainability.
- Ensure the quality, reliability and consistency of the central data warehouse and its data products.
- Use modern AI-assisted development tools, such as Claude Code and GitHub Copilot, to improve development productivity and accelerate coding activities.
Requirements
- Strong experience in data warehousing, including different data architectures and data modelling approaches.
- Excellent SQL skills.
- Strong communication skills in English (C1), with the ability to communicate effectively with both technical and non-technical stakeholders.
- Good collaboration and teamwork skills, with a proactive, delivery-oriented mindset.
Nice to have
- Experience with Data Vault 2.0 methodology.
- Hands-on experience with Snowflake and dbt (Core).
- Experience with Databricks, particularly in the context of data platform migration.
- Experience with Apache Airflow and Python.
- Familiarity with Azure DevOps.
- Comfortable using AI-assisted development tools such as Claude Code and GitHub Copilot.
- German language skills (B2 or higher) are strongly preferred.