Lead Data Engineer - IM

Lead Data Engineer - IM

Must Have Technical/Functional Skills

Data Bricks , EBT ,Airflow , Asset Management exp

Roles & Responsibilities

Lead Data Engineer – Information Management (IM)

Experience

8–15 Years

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Role Overview

We are looking for a highly skilled Lead Data Engineer with strong hands-on experience in Databricks, dbt, and Python, and a proven track record of leading and executing data platform migration and modernization programs. The ideal candidate will have experience migrating legacy data warehouses, ETL platforms, and cloud/on-prem data ecosystems to a modern Databricks Lakehouse architecture using dbt-based transformation frameworks. This is a hands-on leadership role requiring deep technical expertise, solution design capabilities, and the ability to mentor engineering teams while driving enterprise-scale data modernization initiatives.

Key Responsibilities

Data Engineering & Development

• Design, build, and maintain scalable data pipelines using Databricks, PySpark, SQL, and Python.

• Develop and optimize ELT/ETL processes for large-scale data ingestion and transformation.

• Implement robust data quality, monitoring, and reconciliation frameworks.

• Build reusable data engineering components and frameworks.

Data Platform Migration & Modernization

• Lead migration of legacy data platforms, data warehouses, and ETL ecosystems to Databricks Lakehouse.

• Transform existing ETL workloads to modern ELT patterns using dbt.

• Analyze source environments and define migration approaches, roadmap, and execution strategy.

• Drive code conversion, performance optimization, and workload modernization efforts.

Databricks Engineering

Develop solutions leveraging:

• Databricks Lakehouse Platform

• Delta Lake

• Unity Catalog

• Databricks Workflows

• Structured Streaming

• Medallion Architecture (Bronze, Silver, Gold)

Optimize Spark jobs and Databricks workloads for performance and cost efficiency.

dbt Development

• Build and maintain dbt models, macros, tests, and documentation.

• Implement incremental processing and reusable transformation frameworks.

• Establish data lineage, testing, and CI/CD best practices.

• Work closely with business and analytics teams to build trusted datasets.

Leadership & Collaboration

• Lead a team of data engineers and developers.

• Perform code reviews and enforce engineering standards.

• Collaborate with architects, product owners, business analysts, and stakeholders.

• Mentor junior engineers and drive adoption of best practices.