Databricks Platform Engineer
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Role details
Tech stack
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Job description
Design and build Delta Lake tables on Databricks (bronze/silver/gold medallion architecture) for financial datasets (AR, GL, invoices, collections) Build and manage Databricks Genie Spaces - configure semantic models, write GENIE-compatible SQL, and tune NL-to-SQL behavior for finance use cases Develop PySpark and Python-based data pipelines (Databricks Jobs + Workflows) for ERP data ingestion, transformation, and aggregation Integrate Databricks Model Serving with LLMs (Claude, GPT-4, or custom fine-tuned models) for AI-driven insights, anomaly detection, and financial forecasting Build RAG pipelines using Databricks Vector Search over financial documents, contracts, and GL notes Expose Databricks SQL Warehouse endpoints to Python API services and the React frontend Manage Unity Catalog governance - row-level security, column masking, data lineage for finance compliance Deploy infrastructure on AWS (S3 as Databricks external storage, IAM roles, VPC networking, Secrets Manager)
Requirements
Databricks (PySpark, Delta Lake, Jobs/Workflows, SQL Warehouses) - 3+ years Databricks Unity Catalog and governance Databricks Genie Spaces (semantic layer, NL analytics) Python 3.11+ for data engineering and API integration AWS (S3, IAM, VPC, Secrets Manager, optionally Lambda/Glue) LLM integration: Databricks Model Serving, MLflow, or direct API calls to Claude/OpenAI SQL (advanced - window functions, CTEs, query optimization)
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