We are seeking a hands-on Data Engineer experienced in building, maintaining, troubleshooting, and optimizing modern cloud data pipelines., * Design and develop end-to-end data pipelines using Databricks & Snowflake

• Build scalable ETL/ELT workflows using Python, PySpark & SQL
• Develop Databricks notebooks, jobs, Delta Lake tables and workflows
• Build Azure data solutions using ADF, ADLS & Synapse
• Optimize Snowflake queries, clustering, storage, partitioning and materialized views
• Implement data quality and governance processes
• Develop streaming pipelines using Spark Streaming or similar technologies
• Build and maintain CI/CD pipelines for data workflows
• Troubleshoot production pipelines and resolve performance/data-quality issues
• Collaborate with Data Scientists, Analysts, Engineers and Business Stakeholders
• Support data migration initiatives in a fast-paced environment

️ CLIENT SCREENING - PLEASE READ

This client is extremely selective and closely reviews resumes.

Candidates should have genuine, hands-on experience with the technologies listed on their resume and must be able to explain their projects and technical contributions in detail during the interview.

DO NOT add or inflate technologies that the candidate cannot technically explain.

Candidates must confidently demonstrate experience with:

Databricks Snowflake Azure PySpark Python SQL ETL/ELT Data Pipelines

SUBMISSION DETAILS

Please provide:

Updated Resume LinkedIn Profile Current Location Visa Status Availability Confirmation of willingness to work onsite 5 days/week

Long-term opportunity with renewable SOW anticipated through the end of 2027.

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Experience: 3+ Years

MUST-HAVE TECHNOLOGIES

• Strong Python, PySpark & SQL
• Hands-on Databricks & Snowflake
• Strong Azure Data Services experience
• Azure Data Factory (ADF), ADLS & Azure Synapse
• ETL/ELT pipeline development
• Data Lake / Data Warehouse architecture
• Databricks Notebooks, Jobs & Delta Lake
• Data Modeling: Star Schema, Snowflake Schema & Dimensional Modeling
• Orchestration: Airflow, dbt, Luigi or similar
• Git & CI/CD
• Jenkins or similar CI/CD tools
• Data Quality, Governance, Security & Compliance

NICE TO HAVE

• Palantir Foundry
• Unity Catalog
• Spark Streaming / Real-Time Data Pipelines
• IBM watsonx.data or similar AI data platforms
• Apache Iceberg / Lakehouse technologies
• GenAI / RAG / LangChain
• MCP (Model Context Protocol)