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Data Engineering Manager

Job in Greenville, Greenville County, South Carolina, 29610, USA
Listing for: STEM Search Group
Full Time position
Listed on 2026-09-13
Job specializations:
  • IT/Tech
    Data Engineering, Data Warehousing
Salary/Wage Range or Industry Benchmark: 140000 - 190000 USD Yearly USD 140000.00 190000.00 YEAR
Job Description & How to Apply Below
  • Act as the hands-on technical architect for the data platform, making real architecture and design decisions since there is no separate architect role on the team
  • Lead and coach a small, close-knit data engineering team, staying hands-on with pipeline design, code review, and day-to-day problem solving
  • Own the technical roadmap for migrating core data infrastructure to Snowflake, driving decisions on schema design, performance, and scalability
  • Modernize ELT/transformation workflows using tools like dbt, Coalesce, or similar, retiring legacy processes as the platform evolves
  • Guide reporting and BI strategy across tools such as Tableau and Sigma so dashboards and data models scale with the new environment
  • Coach and develop team members through regular 1:1s and hands-on pairing, stepping in to "coach up" where skill gaps exist
  • Partner directly with business stakeholders to translate reporting needs into scalable, well-architected data solutions
What we're looking for...
  • Hands-on data engineering architecture experience: someone comfortable owning schema design, performance tuning, and platform tradeoffs without a dedicated architect to lean on
  • Strong working knowledge of Snowflake, or a comparable cloud data warehouse with fast ability to ramp
  • Experience with modern ELT/transformation tooling such as dbt, Coalesce, or similar platforms
  • Experience with Tableau or a comparable BI tool
  • A genuine "player-coach" leadership style: someone who leads by doing, not just delegating
  • Strong interpersonal skills and a real investment in team culture, mentorship, and cross-functional relationships
  • Nice to have:
    Azure experience, Sigma, Streamlit, or exposure to legacy Microsoft data stacks (SQL Server, SSIS) is a plus but not required
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