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Data Engineer

Job in Milton, Fulton County, Georgia, USA
Listing for: Perform
Full Time position
Listed on 2026-02-28
Job specializations:
  • IT/Tech
    Data Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

We’re hiring a Data Engineer to join a product development team that builds web and mobile software. Our environment is collaborative and service-oriented with high expectations for quality, speed, and ownership. This role is heavily focused on data migrations, backend data movement, and data quality. You’ll design and execute migrations between systems and build the pipelines, services, and tooling needed to move, validate, and reconcile data safely in production.

What

You’ll Be Doing
  • Design and execute data migrations between systems:
    • source-to-target mapping
    • transformations
    • validation and reconciliation
    • resolving data quality issues
  • Build and maintain production data movement services and scripts (Python-heavy)
  • Develop and support backend pipelines, APIs, and internal data management tools
  • Partner with engineers to ship migrations end-to-end: design → deploy → test → monitor → support
  • Contribute to migration test strategy, automation, and performance improvements
What You Bring
  • 5+ years shipping production software solutions
  • Strong Python experience delivering production pipelines or backend services
  • Hands‑on experience executing real data migrations in production environments
  • Strong SQL and No

    SQL experience in production
  • Strong data modeling skills:
    • Analyze source/target schemas
    • Write complex queries
    • Design migration-friendly data structures
  • Comfortable working with JSON, REST APIs, and data validation tooling
  • Strong attention to detail, problem‑solving ability, and communication skills
  • Experience working in Git‑based workflows
How You’ll Succeed
  • Azure data ecosystem experience (or comparable cloud stack), such as:
    • Data orchestration tools
    • Data lake / warehouse patterns
    • Tabular models / semantic layers
  • Experience with SQL Server and Mongo

    DB specifically
  • Automated deployment of pipelines and schema changes
  • CI/CD experience for data systems
  • Strong opinions and experience around data quality, testing, and automation
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