Fulltime - Databricks Engineer

Role : Databricks Engineer

Location : McLean, VA (100% Onsite

Data Platform, Cloud Migration, ETL/ELT

Secondary : AI/ML, Python

Role Summary

Lead Data Engineer responsible for designing, migrating, and optimizing enterprise-scale data platforms on Microsoft Azure, with strong hands-on ownership of ETL/ELT pipelines, cloud data warehousing, and data integration across heterogeneous sources.

Key Responsibilities

Lead data migration initiatives to Azure, including on prem to cloud and legacy ETL modernization.

Design, build, and maintain scalable ETL/ELT pipelines using Azure Data Factory, Databricks (PySpark), and Informatica (PowerCenter / IICS).

Implement end to end data ingestion, transformation, and loading into Azure Data Lake Gen2, Azure SQL, Azure Synapse, and Snowflake.

Migrate and refactor existing ETL workflows (Informatica / SSIS) to cloud native Azure architectures.

Optimize data pipelines for performance, reliability, and cost efficiency.

Ensure data quality, governance, security, and compliance during migration and ongoing operations.

Collaborate with architects, business stakeholders, and downstream analytics teams.

Required Skills

Azure Migration: Hands on experience with Azure Data Lake (Gen1/Gen2), Azure Data Factory, Azure Databricks, Azure Synapse, Azure SQL

ETL/ELT: Strong expertise in Informatica PowerCenter, Informatica IICS, ETL design, CDC, SCDs, and batch/stream processing

Programming: Python, PySpark, SQL, PL/SQL

Databases & Warehousing: Oracle, SQL Server,

Cloud DevOps: Azure DevOps CI/CD pipelines, Git-based version control

Data Modeling: Star schemas, dimensional modeling

Nice to Have

AI/ML experience

Power BI / semantic modelling exposure