Lead Data Engineer - PySpark/SQL/AI

Lead enterprise-scale modernization initiatives from legacy data warehouses and ETL platforms to cloud-native data ecosystems.

Design and implement modern Lakehouse architectures using Medallion (Bronze, Silver, Gold) data design principles.

Develop scalable and secure data platforms supporting batch, streaming, and real-time processing workloads.

Drive architecture decisions involving Data Lake, Data Warehouse, Lakehouse, Data Mesh, and Data Fabric patterns.

Design, develop, and optimize large-scale data pipelines using: Python Apache Spark / PySpark SQL ETL/ELT frameworks

Python

Apache Spark / PySpark

SQL

ETL/ELT frameworks

Implement cloud-native solutions leveraging platforms such as: Microsoft Fabric Establish engineering standards for reliability, scalability, observability, and cost optimization.

Microsoft Fabric

Establish engineering standards for reliability, scalability, observability, and cost optimization.

Lead large-scale migration programs involving: Legacy Data Warehouses On-Prem Hadoop/Cloudera Platforms Traditional ETL Middleware

Legacy Data Warehouses

On-Prem Hadoop/Cloudera Platforms

Traditional ETL Middleware

Develop migration strategies including assessment, planning, automation, reconciliation, testing, and cutover execution.

Ensure business continuity and data integrity during migration programs.

*Job posting may come down early due to volume of applicants.

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