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Forward Deployed Engineer - Databricks
Skills
Warehouse OperationsAmazon Web ServicesBronzeData WarehousingHandoverOptimizationPermissions
What the job involves
The main requirements, responsibilities and hiring steps.
Requirements
- 4+ years of experience in data engineering platform engineering analytics engineering or technical consulting
- Demonstrable experience owning at least 2 end-to-end Databricks implementations in production
- Strong production experience with PySpark and SQL
- Experience with Databricks Lakeflow notebooks repos SQL Warehouses and cluster/serverless compute patterns
- Solid understanding of distributed computing concepts including partitioning shuffling and optimisation techniques
- Practical experience with cloud data platforms on at least one major provider ideally both Azure and AWS including storage networking and security basics
- Good knowledge of data warehousing and Lakehouse patterns
- Experience with CI/CD and modern SDLC including Git-based workflows code reviews deployment pipelines and infrastructure as code is a plus
- Strong problem solving skills and ability to debug complex data issues across multiple systems
- Confident communicator able to translate technical detail into business language for non technical stakeholders
- Self driven curious and committed to continuous learning in data engineering cloud and analytics
- Familiarity with data governance security and compliance in regulated environments
Nice to have
- Self-driven
- Curious
- Communicative
- Collaborative
- Detail-oriented
Day to day
- Embed with customer teams to design and deliver production Databricks solutions.
- Build robust data pipelines using PySpark SQL Delta Lake and Databricks Workflows.
- Implement Lakehouse architecture and Unity Catalog governance patterns while supporting migration and deployment activities.