Data Engineer

• Design and develop scalable data pipelines using Palantir Foundry, Databricks, and Snowflake
• Build ETL/ELT workflows using Python, PySpark, and SQL
• Develop Azure-based data solutions using ADF, ADLS, Synapse, and Databricks
• Support enterprise data migration and modernization initiatives
• Implement data quality, governance, metadata, and lineage
• Optimize Spark/Databricks workloads and Snowflake queries
• Develop dimensional data models and analytical datasets
• Support batch and near-real-time data pipelines
• Troubleshoot production pipeline, data quality, and performance issues
• Implement CI/CD and collaborate with data scientists, analysts, and business stakeholders

Preferred / Nice-to-Have

• Delta Lake / Apache Iceberg
• Unity Catalog
• Kafka / Spark Streaming / Azure Event Hubs
• Snowflake clustering and materialized views
• IBM WatsonX.data or similar AI data platforms
• GenAI / RAG / LangChain
• MCP

• 3+ years of hands-on Data Engineering experience
• Strong Python, PySpark, and SQL
• Hands-on Databricks experience
• Strong Snowflake experience
• Azure experience with ADF, ADLS Gen2, Synapse, and Databricks
• Hands-on Palantir Foundry experience
• ETL/ELT pipeline development
• Data modeling - Star Schema / Snowflake Schema
• Airflow, dbt, or similar orchestration tools
• Data quality, governance, metadata, and security
• Git and CI/CD
• Batch and/or streaming data pipelines