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# Data Engineer

- **Company:** Infosys
- **Location:** Charlotte, NC, United States
- **Experience:** Expert
- **Salary:** $100,000.0 - $130,000.0
- **Contract:** Permanent contract
- **Skills:** Agile Methodology, BigQuery, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Systems, Data Warehousing, Query Optimization, SQL Databases, Teradata SQL, Enterprise Data Management, Google Cloud, Ab Initio, Data Management, Data Pipelines
- **Published:** August 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=d0dbd2fcacaa6d5a

## About the Role

* 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.

## Description

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., * 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.


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