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Job Description
Structured overview of role & requirementsAbout This Role
Design, build, and maintain production-grade data ingestion and transformation pipelines using Databricks, PySpark, and Delta Lake.
Integrate multiple enterprise source systems including ERP, planning, and HR into Databricks environments with Microsoft Fabric integration.
Develop and implement AI agents and MCP servers using Python, ensuring secure and governed access, along with data quality, lineage, and governance adherence.
Minimum Requirements
Minimum 7 years of experience in Data Engineering.
At least 3 years of hands-on experience with Databricks including Databricks Workflows, Unity Catalog, and Delta Lake.
Proficient in PySpark, SQL optimization, dimensional data modelling (star schemas), and Slowly Changing Dimensions (SCD).
Experience integrating Databricks with Microsoft Fabric and understanding of Microsoft OneLake and Fabric Lakehouses.
Ideal Candidate Profile
Experience in Finance, FP&A, or financial data engineering with knowledge of GL structures, budgets, forecasts, and TBM classification frameworks.
Proven experience building AI-powered data engineering solutions and agentic workflows involving LLM frameworks such as LangChain or LangGraph.
Familiarity with enterprise AI governance, secure AI/data access, data governance, lineage, and automated data reconciliation in Microsoft Fabric-based analytics environments.