Azure Data Engineer with Databricks

As a Data Engineer on our team, you’ll design and build ETL/ELT pipelines in a modern Lakehouse architecture using medallion principles (raw * refined * presentation).

You’ll work with Databricks to develop apps, dashboards, and Genie Spaces that support analytics and operational needs across the organization.

You’ll also collaborate closely with business stakeholders and our Data Governance team to define appropriate data domains and shape high quality data products.

This is a hands on role in a cutting edge environment with continuous deployments, rapid iteration, and a culture that encourages challenging assumptions and thinking creatively.

What You’ll Do

• Build, optimize, and maintain ETL/ELT pipelines within a modern Lakehouse using medallion architecture.
• Create ingestion pipelines using Lakeflow Jobs and Lakeflow Connect to bring new data sources into the Databricks Lakehouse efficiently and reliably.
• Use Databricks Declarative Pipelines to design and deliver scalable, governed data products.
• Develop Databricks Apps, Dashboards, and Genie Spaces that drive business insights and operational efficiency.
• Work in a continuous deployment environment using Azure DevOps, delivering updates and improvements throughout the day.
• Partner with business stakeholders to understand requirements and translate them into scalable data solutions.
• Collaborate with Data Governance to define data domains, ensure data quality, and shape enterprise data products.
• Contribute to a high performance engineering culture that values innovation, experimentation, and challenging the status quo., * Opportunity to work with cutting edge tools and architectures in a rapidly evolving data ecosystem.
• A contract to hire path that lets both you and the team ensure a great long term fit.
• High autonomy, fast iteration cycles, and meaningful ownership of data products used across the organization.
• A team culture built around curiosity, innovation, and continuous improvement.

• Strong Python and SQL skills - these are required.
• Experience with Databricks is strongly preferred, but experience with big data platforms such as Snowflake can be a strong substitute.
• Familiarity with modern data engineering concepts: Lakehouse architecture, Delta tables, CI/CD, distributed compute, orchestration.
• Ability to think creatively, propose new approaches, and question existing patterns.
• Strong communication skills and comfort working with both technical and non technical stakeholders.