Databricks Data Engineer

About the role

We are looking for a Databricks Data Engineer to design, build, and operate scalable data pipelines and curated data products on the Databricks platform. You will work across ingestion, transformation, governance, and delivery layers using SQL, Python, and PySpark while applying strong data‑warehousing principles.

Key responsibilities

• Build and maintain production‑grade data pipelines in Databricks using SQL, Python, and PySpark.
• Implement ELT/ETL patterns for batch and, where relevant, streaming data processing.
• Develop and maintain lakehouse data models and curated datasets aligned with Kimball, Inmon, or Data Vault best practices.
• Use Databricks‑native capabilities such as Lakeflow Declarative Pipelines (DLT) to create robust, maintainable pipelines.
• Implement data quality checks (Expectations) and monitoring to ensure reliability of data products.
• Configure and manage governance and access controls with Unity Catalog, including catalogs, schemas, permissions, and lineage‑friendly practices.
• Optimize performance and cost through cluster sizing, partitioning, caching, and query optimization.
• Collaborate with analytics, data‑science, and engineering stakeholders to define data contracts and deliverables.
• Create and maintain technical documentation and operational runbooks.
• Support operational excellence through incident response, root‑cause analysis, and continuous improvement.

Required profile

• Proven hands‑on experience with Databricks in production environments.
• Strong working knowledge of SQL, Python, and PySpark for data‑engineering workloads.
• Practical experience with Databricks‑specific technologies: Lakeflow Declarative Pipelines, Expectations, Unity Catalog.
• Solid understanding of data‑warehousing design and modeling methodologies (Kimball, Inmon, Data Vault).
• Knowledge of data‑engineering fundamentals such as orchestration patterns, incremental processing, SCDs, metadata management, and observability.

Required skills

• Databricks platform
• SQL
• Python
• PySpark
• Lakeflow Declarative Pipelines (DLT)
• Expectations / data‑quality validation
• Unity Catalog
• Data‑warehousing (Kimball, Inmon, Data Vault)
• Microsoft SQL Server / T‑SQL (nice‑to‑have)
• Azure services (ADLS, networking, security, identity)
• Git‑based workflows and CI/CD for data pipelines

What we offer

• Competitive monthly salary of €5,500 (B2B contract)
• Opportunity to work with cutting‑edge data‑lakehouse technologies
• Collaborative environment with analytics and data‑science teams