Data Engineer - Remote
Mindex
·Yesterday
- Salary
- $90k – $140k/yr
- Location
- Rochester, New York
- Workplace
- Remote
- Type
- Full-time
- Department
- SOW
- Experience
- 3+ years
- Visa
- Not sponsored
- Source
- Workable
Description
Mindex is looking for Data Engineers to join a focused migration team moving Informatica pipelines into Maia (Matillion) and Snowflake. You’ll convert, test, and verify pipelines across an estate of roughly 1,500-1,700 pipelines, build reusable components that speed up each conversion, and partner with our client on validation and cutover readiness. The ideal candidate has strong ETL/ELT fundamentals, advanced SQL and Python skills, and communicates clearly with technical and non-technical stakeholders.
We welcome candidates from a variety of locations; however, all candidates should be open to occasional in-person participation for business meetings, team events, or collaboration opportunities. Candidates located within approximately 35 miles of Rochester, NY may be asked to work from the office more frequently based on business or team needs.
Compensation
$90,000 - $140,000
What You’ll Accomplish
- Convert Informatica pipelines to Maia (Matillion) and Snowflake using the Solution Lead’s factory-style patterns, and build reusable shared jobs, templates, and validation utilities.
- Speed up conversions by removing bottlenecks and manual steps, verifying AI-generated output, and folding proven improvements into the team’s shared patterns.
- Design and optimize Snowflake pipelines and downstream objects for performance, reliability, and ease of operation.
- Build and support ingestion pipelines for on-premises and Azure SQL Server, files, APIs, and MongoDB.
- Profile source data and investigate legacy behavior to uncover edge cases, using SQL and Python to compare outputs with legacy results and resolve discrepancies.
- Agree on migration sequencing, testing standards, and sign-off criteria with technical leads and client SMEs.
- Document migration logic, assumptions, test evidence, and go-live readiness so stakeholders can review and verify decisions.
- Build an efficient, repeatable workflow and communicate progress and risks early and often to keep the team on track for key project milestones.
- Demonstrate an AI-first mindset by effectively leveraging AI-assisted tools and technologies to enhance productivity, accelerate problem-solving, improve quality, automate routine tasks, and drive innovation in the delivery of solutions and services.