Design and implement medallion architecture (Bronze/Silver/Gold) using Databricks
Develop automated data pipelines from multiple sources to analytics-ready formats
Create robust ETL/ELT workflows with Apache Spark for batch and streaming
Build data quality monitoring and validation across the data/ML lifecycle
Implement MLOps including automated model training, validation, deployment, and monitoring
Design scalable ML inference systems for high-volume, low-latency production

🎯 Requirements

5+ years in data engineering, incl. 3+ years building production pipelines on Databricks
Python, PySpark, Spark SQL with medallion architecture and modern data patterns
Production ML systems: deployment, monitoring, and MLOps in cloud environments
Data architecture expertise with scalable processing and governance frameworks
Experience integrating with Qlik, Tableau, PowerBI, Palantir Foundry (MAVEN)

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