Principal Data Platform Engineer (Databricks)

In4ge is a recruitment company focused on connecting talented employees with suitable companies to foster growth and success. The role is for a key technical position in developing a platform supporting tax advisory services, combining Tech Lead and Team Lead responsibilities with real impact on technology direction and engineering team work.

• Minimum 12 years of IT experience in corporate, global environments.
• Very good English proficiency (minimum B2).
• Strong software engineering fundamentals (preferred over purely data/BI profiles).
• Experience with lakehouse platforms (Databricks), streaming/near real-time architectures, Databricks Structured Streaming, Delta Live Tables.
• Knowledge of integration with Power BI, Microsoft Azure/M365 environment, Azure services (Functions, Service Bus/Event Hub, App Services, Cosmos DB), MongoDB.
• Experience in DevOps/DataOps: CI/CD, Infrastructure as Code.
• Experience with AI tools supporting development (e.g., GitHub Copilot, Codex, Claude, Gemini).
• Ability to work in ambiguous environments and build solutions from scratch.
• Comfortable in platform and architectural environments.
• Ability to combine technology with leadership.
• Experience in modern data platforms.
• Understanding of streaming-first approach beyond classic ETL/batch processing.
• Ability to influence technical direction of multiple teams.

Platform Databricks:

• Act as Tech Lead for the development of the Databricks Lakehouse platform.
• Support teams in building data products (best practices, patterns, tools).
• Design abstraction layers and frameworks to simplify developers' work.
• Develop the platform following a developer-first approach (beyond classic ETL).

Modern Data Architecture (Streaming):

• Develop architecture based on streaming and event-driven approaches.
• Support transformation from classic batch data warehouses to modern solutions.
• Make architectural decisions regarding performance, scalability, and reliability.

DevOps & Infrastructure:

• Implement DevOps/DataOps approaches (CI/CD, Infrastructure as Code).
• Co-responsible for infrastructure decisions related to the platform.
• Monitor and optimize Databricks costs.
• Collaborate on platform scaling and governance.

Technology Integrations:

• Integrate Databricks with tools such as Power BI, Microsoft Fabric, and other data consumption systems.
• Support teams at the intersection of data platform and BI.

Leadership:

• Lead teams (DevOps, platform engineers, Power BI support).
• Mentor and develop engineers.
• Define technical direction for the platform.
• Collaborate with business and stakeholders on strategy implementation.