Data Quality Engineer

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.