Lead Data Quality Engineer - Automation & CI/CD Validation

Cognizant; Chicago (IL); Hybrid; USD 71,000 - 113,000; Full time

Benefits offered by this job

Medical/Dental/Vision/Life Insurance

401(k) plan and contributions

Paid holidays and PTO

Long-term/Short-term Disability

Parental Leave

Employee Stock Purchase Plan

Job summary

Cognizant is seeking a Lead Data Quality Engineer - Automation Testing with CI/CD to drive data quality assurance for large-scale data platforms in a Retail Marketing Technology setting. The role emphasizes automated validation, data pipeline testing, and integrating quality controls into CI/CD to ensure data accuracy and reliability.

The ideal candidate will lead cross-functional collaborations, design scalable testing solutions, and contribute to monitoring and alerting for data quality across

Qualifications

• Experience in testing data pipelines for accuracy, freshness, and integrity.
• Ability to embed quality checks within CI/CD workflows.
• Familiarity with vector databases and Retrieval‑augmented generation (RAG) systems.

Responsibilities

• Coordinate with upstream and downstream integration partners.
• Design automated testing frameworks to validate data across pipelines.
• Test ETL logic to ensure transformations meet business requirements.
• Profile raw data to identify anomalies and quality issues.
• Set threshold alerts to catch bad data before production.
• Embed quality checks in deployment workflows to block faulty code.

Skills

Data Quality Testing

CI/CD

Automation Testing

ETL Validation

Data Profiling

Vector Databases

Tools

Vector Databases

RAG Systems

CI/CD Tools

Job description

Cognizant is seeking a Lead Data Quality Engineer - Automation Testing with CI/CD to drive data quality assurance for large-scale data platforms in a Retail Marketing Technology setting. The role emphasizes automated validation, data pipeline testing, and integrating quality controls into CI/CD to ensure data accuracy and reliability.

The ideal candidate will lead cross-functional collaborations, design scalable testing solutions, and contribute to monitoring and alerting for data quality across