Designs and maintains enterprise ETL and data integration pipelines, develops scalable data warehouse solutions, optimizes SQL and data workflows, and supports migration of legacy platforms to Google Cloud. The role focuses on data quality, performance, reliability, troubleshooting, and collaboration with technical and business stakeholders.
Data Engineer
Location: Charlotte, NC (Hybrid)
Schedule: Full-Time | Hybrid (3 days onsite)
Interview Process: In-Person Interview Required
We are seeking a Data Engineer to join a team focused on modernizing enterprise data platforms and supporting cloud migration initiatives. This is a hands-on role where you'll design and build scalable data pipelines, optimize data workflows, and help transition legacy data environments to Google Cloud.
Responsibilities- Design, develop, and maintain enterprise ETL/data integration pipelines.
- Build and optimize data solutions using GCP, BigQuery, Ab Initio, and Teradata.
- Support migration of legacy data platforms to Google Cloud.
- Develop and optimize SQL queries, data models, and data warehouse solutions.
- Ensure data quality, performance, and reliability across enterprise systems.
- Collaborate with architects, developers, analysts, and business stakeholders to deliver scalable data solutions.
- Troubleshoot and resolve data integration and performance issues.
- 5+ years of experience in Data Engineering, ETL Development, or Data Integration.
- Hands-on experience with GCP, BigQuery, Ab Initio, and/or Teradata.
- Strong SQL development and query optimization skills.
- Experience building and maintaining enterprise data pipelines.
- Understanding of data warehousing concepts and ETL best practices.
- Excellent communication and problem-solving skills.
- Experience supporting cloud migration initiatives.
- Background working in large enterprise or regulated environments.
- Familiarity with Agile development methodologies.
If you're passionate about building scalable data solutions and working on enterprise cloud modernization initiatives, we'd love to connect.
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