Lead Engineer

Job Title: Data Engineering Lead –

Role Summary: We are looking for a Data Engineering Lead to lead a team of data engineers in building and delivering scalable ingestion and transformation pipelines on Databricks + AWS, ensuring engineering execution aligns with the platform's architecture and delivery timelines.

Key Responsibilities

• Lead a team of Data Engineers delivering Bronze/Silver/Gold pipelines across batch, near-real-time, streaming, and CDC patterns
• Drive hands-on implementation and code/design reviews for ingestion pipelines (AWS Glue, DMS, DataSync) and streaming jobs (Kinesis, Kafka, or Databricks Structured Streaming)
• Own sprint planning, task allocation, and delivery tracking for the engineering pod
• Ensure adherence to Unity Catalog governance standards, data quality checks, and orchestration best practices (Airflow/MWAA)
• Troubleshoot complex pipeline/performance issues and mentor junior engineers
• Collaborate closely with the Data Architect to translate architecture into engineering execution
• Support client/stakeholder updates on engineering progress and technical blockers

Must-Have Skills

• 7–10 years in data engineering, including 2+ years leading a team/pod
• Strong hands-on Databricks/Spark, Delta Lake, SQL, and Python/PySpark expertise
• Strong AWS data services experience: Glue, S3, DMS; working knowledge of Kinesis/MSK or Kafka
• Solid understanding of medallion architecture, CDC ingestion, and orchestration tools
• Proven ability to manage delivery timelines and mentor a team

Good-to-Have: Exposure to vector databases, RAG pipeline data prep, or agentic/AI tooling (Bedrock, Mosaic AI).