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# Technical Test Data lead

- **Company:** SOGETI
- **Location:** Chicago, IL, United States
- **Experience:** Expert
- **Salary:** $110,000.0 - $125,000.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Automation of Tests, Information Systems, Data Validation, Extract Transform Load (ETL), Data Mapping, Data Transformation, Data Warehousing, Database Testing, JSON, Azure Data Lake, Simple Data Format, Software Engineering, Extensible Markup Language (XML), Performance Testing, Data Lakes, Semi-structured Data, Information Technology, Data Pipelines, Mulesoft
- **Published:** June 9, 2026
- **Apply:** https://www.dice.com/job-detail/e7043e48-637f-40fa-ac30-d3e3e6b1993f

## About the Role

* Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems, Business Administration, or a related field.

## Description

* Lead end-to-end data testing strategy, planning, and execution for data warehouses, data lakes, ETL/ELT pipelines, reporting, and analytics platforms
 * Define and implement data test frameworks, test scenarios, and validation rules for structured and semi-structured data
 * Validate data accuracy, completeness, consistency, timeliness, and reconciliation across source-to-target systems
 * Review and approve data mapping documents, business rules, and transformation logic
 * Coordinate data testing activities across upstream and downstream systems
 * Lead defect identification, root cause analysis, prioritization, and resolution tracking
 * Collaborate closely with Data Engineers, QA teams, Business Analysts, Product Owners, and SMEs
 * Ensure data testing aligns with regulatory, audit, and governance standards, where applicable
 * Provide status updates, reporting, and risk assessments to project and program leadership
 * Mentor and guide junior data testers and QA resources

What you will bring:

 * Strong data testing experience - Understanding of requirements, data mapping validation, data transformation rules, and downstream validation
Technical understanding of the platforms and files - Azure Data Lake, MuleSoft, Databus, handling of different file formats, JSON, XML etc
Building custom queries for data validation between different types of sources and target systems
Understanding of historical data validation, full data, and incremental data validations
Performance testing for batch jobs - Understanding of current state requirements, development of workload models, associated metrics, baseline vs actual comparison reports etc.


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