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Data Quality Engineer

Job in Peoria, Peoria County, Illinois, 61639, USA
Listing for: Swoon
Full Time position
Listed on 2026-06-12
Job specializations:
  • Engineering
Salary/Wage Range or Industry Benchmark: 28 USD Hourly USD 28.00 HOUR
Job Description & How to Apply Below

We are looking for a Data Quality Engineer for one of our leading engineering clients in Peoria, IL.

Title:

Data Quality Engineer

Location:

Open to Chicago, IL or Peoria, IL - both 100% onsite (preference first goes to local candidates, open to non-local candidates who can 100% relocate 2 weeks from offer and be onsite day 1 at their own cost)

Type:
Contract

Pay: range $28/hour on W2 - no flex, exact rate

Length: 12 months - possibility to extend

Screenings: no tech, full panel drug and background once hired

+optional benefits, long term contract with ability to extend

Must haves
  • Education & Experience

    Required:

    1-2 years experience in software test and/or software development
  • (Required) SQL (Snowflake)
  • Java/Springboot
  • AWS (or other cloud services)
Soft Skills
  • (Required) Critical and Analytical thinking
  • Strong communication
  • Detail Orientated
  • Quality Focus
Job Overview

This role is within the Data Test team to support quality across data pipeline, workflows and platform operations. This role focuses on creating and executing tests to meet data quality standards and rules. The position works closely with data engineering teams and data stewards to troubleshoot issues, improve data quality and processes.

Position’s Contributions to Work Group
  • Builds and executes tests for data pipelines to ensure data accuracy, reliability, and quality across platform processes.
  • Supports operational monitoring and issue resolution to maintain stable and efficient data flow.
  • Identifies defects, validates fixes, and partners with cross-functional teams to improve data quality and reduce production risk.
  • Helps improve team efficiency by supporting repeatable test practices, operational readiness, and continuous process improvement.
Typical task breakdown
  • Test design and execution
  • Defect identification and validation
  • Root Cause Analysis and process improvements
  • Cross-functional collaboration between Data Engineering and Data Stewards
Interaction with team
  • Team is Helios data test, working with roughly 5 individuals. Plus 2 leads/mgr from data engineering.
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