Senior Databricks Engineer

Job Description & Summary

PwC is a global network of more than 370,000 professionals in 149 countries that turns challenges into opportunities. We create innovative solutions in audit, consulting, tax and technology, combining knowledge from all over the world.

PwC SDC Lviv, opened in 2018, is part of this global space. It is a place where technology is combined with team spirit, and ambitious ideas find their embodiment in real projects for Central and Eastern Europe.

What do we guarantee?

• Work format: Remote or in a comfortable office in Lviv - you choose.
• Development: Personal development plan, mentoring, English and Polish language courses.
• Stability: Official employment from day one, annual review of salary and career prospects.
• Corporate culture: Events that unite the team and a space where everyone can be themselves.

We seek a Senior Data Engineer – Databricks & dbt to build and maintain scalable data pipelines and transformation solutions on Azure Databricks.
This hands-on role focuses on Databricks, dbt, SQL, Python/PySpark, Lakehouse architecture, data quality, and reliable end-to-end data delivery.

Main Responsibilities:

• Build, test and maintain data pipelines on Databricks using SQL, Python and PySpark.
• Build Python integrations for source APIs, custom ingestion, reusable components and internal tooling.
• Apply Bronze/Silver/Gold modelling principles.
• Develop and maintain the dbt transformation layer, including models, sources, snapshots, tests, contracts, data-quality controls and documentation.
• Translate business logic into modular and performant staging, intermediate and mart models.
• Monitor data quality, source freshness and failed runs.
• Orchestrate workflows using Databricks Workflows/Lakeflow and dbt.
• Work with Unity Catalog, access controls, ownership, lineage and cost governance.
• Collaborate with the Data Architect and Technical Lead.
• Contribute to platform standards, patterns, tooling and peer code reviews.
• Work within Git-based CI/CD processes across DEV, UAT and PROD.
• Support integrations with Azure SQL and, where relevant, Azure Data Factory.
• Explore AI use cases on Databricks, including MCP-based interfaces and Databricks Apps.
• Ideally help coach junior Data Engineers.

Key Requirements:

• At least 2 years’ hands-on data or analytics engineering experience.
• Production experience with Azure Databricks.
• Demonstrable delivery experience with dbt Core or dbt Cloud.
• Experience delivering work items end to end within a structured delivery team.
• Advanced SQL and analytical/dimensional data modelling.
• Python and PySpark, including modular, testable API integrations.
• Databricks Lakehouse architecture and Bronze/Silver/Gold patterns.
• Databricks Asset Bundles.
• Databricks Workflows/Lakeflow.
• Strong dbt knowledge: incremental models, snapshots, Jinja, macros, tests, contracts, exposures and documentation.
• Git, CI/CD and DevOps practices.
• Understanding of Unity Catalog, governance and data ownership.
• English is required.

Valuable additional experience:

• Technical-lead or senior-contributor experience.
• Running and troubleshooting dbt on Databricks.
• Azure Data Factory.
• Databricks AI capabilities, MCP servers or assistant-based interfaces.
• Databricks Apps.
• Power BI and semantic data modelling.
• Coaching junior engineers

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