Data Engineer (Databricks)

We are looking for a Data Engineer with solid Databricks experience to design, build and operate data pipelines on a Lakehouse architecture. You will join a data team and work closely with analysts, data scientists and business teams.

The focus is the Databricks platform: ingesting, transforming and serving reliable, governed and well-performing data. Experience with Azure and Microsoft Fabric is a secondary requirement, relevant for integration with the wider data ecosystem.

Responsibilities

• Design and implement batch and streaming data pipelines on Databricks, using PySpark and Spark SQL.

• Build and maintain a layered Lakehouse architecture (medallion: bronze, silver, gold) on Delta Lake.

• Develop declarative pipelines and orchestrate workloads with Lakeflow (Delta Live Tables, Jobs/Workflows).

• Implement data governance with Unity Catalog: catalogs, permissions, lineage and auditing.

• Model data for analytical consumption and make it available to BI and Data Science teams.

• Document solutions and contribute to the team's engineering standards and best practices.

Required qualifications

• 3+ years of experience as a Data Engineer, including at least 2 years on Databricks projects in production.

• Strong command of Apache Spark (PySpark and Spark SQL) and Python.

• Advanced SQL, including query optimization and data modeling (dimensional and Lakehouse).

• Hands-on experience with Delta Lake and the medallion architecture.

• Experience with Unity Catalog, access management and governance.

• Experience orchestrating pipelines on Databricks (Jobs/Workflows, Delta Live Tables).

• Working practice with Git, CI/CD and test-driven development in data projects.

• Knowledge of stream processing (Structured Streaming, Auto Loader).

Secondary requirements

Azure

• Azure Databricks and Azure Data Lake Storage Gen2.

• Azure Data Factory for ingestion and orchestration.

• Security and identity: Microsoft Entra ID, Key Vault, managed identities and private networking.

• Azure DevOps (Repos and Pipelines).

Nice to have

• Databricks certifications (Data Engineer Associate or Professional).

• Experience with dbt, Terraform or other infrastructure-as-code tools.

• Experience migrating to Databricks from legacy platforms (SQL Server, Synapse, Hadoop).

• Knowledge of MLflow and of supporting Machine Learning and AI use cases.

Benefits

• Remote work

• Food ticket

• Health insurance

• Training and access to certification vouchers

• Work-life balance initiatives

• Referral program

• Birthday off

• Give back day – enjoy a day to give back to society!