Job Overview
We are looking for an experienced Data Engineer – Data Warehouse to support the modernization of enterprise data platforms within a large financial services environment.
The ideal candidate will have strong hands-on experience with Snowflake, dbt, DataStage, and Control-M, along with a solid understanding of data modeling and enterprise data engineering best practices.
Key Responsibilities
- Design, develop, and maintain end-to-end data pipelines, from data ingestion through consumption.
- Support the migration of legacy ETL workflows into a modern, cloud-native data platform.
- Build and optimize data warehouse structures using dimensional modeling techniques.
- Implement and maintain data models such as Star Schema, Snowflake Schema, and Slowly Changing Dimensions (Type I & II).
- Work closely with business and technical teams to translate data requirements into scalable engineering solutions.
- Identify and manage risks related to data processing in compliance with financial services policies and standards.
- Develop and maintain CI/CD pipelines for data deployments using Git and Azure DevOps.
- Ensure reliability, performance, and data quality across enterprise data products.
- Collaborate with cross-functional teams to support highly visible and business-critical data initiatives.
Required Skills & Experience
- Strong experience as a Data Engineer supporting enterprise data warehouse platforms.
- Hands-on experience with:
- Snowflake
- Dbt
- IBM DataStage
- Control-M
- Solid understanding of data warehouse design and dimensional modeling.
- Experience building and maintaining automated data pipelines.
- Familiarity with CI/CD practices for data engineering.
- Experience working in regulated or large enterprise environments is a plus.
- Strong analytical, problem-solving, and communication skills.