Job Summary
We are seeking a Lead Data Quality Engineer - Automation Testing with CI/CD to drive data quality assurance initiatives for large-scale data platforms within a Retail Marketing Technology environment. The ideal candidate will bring strong expertise in automated data validation, data pipeline testing, and CI/CD quality integration to ensure the accuracy, integrity, and reliability of critical business data. This role requires close collaboration with cross-functional teams and integration partners to establish quality standards, identify data issues early, and implement scalable quality controls across the data lifecycle.
*Please note, this role is not able to offer visa transfer or sponsorship now or in the future*
About the Role
As a Lead Data Quality Engineer, you will play a key role in ensuring the health, reliability, and compliance of data pipelines that support business-critical applications and analytics. You will lead efforts to design and implement automated testing solutions that validate data freshness, integrity, and transformation accuracy across complex data ecosystems.
In this role, you will work closely with upstream and downstream integration partners, data engineering teams, and business stakeholders to validate data flows, troubleshoot quality issues, and establish proactive monitoring and alerting mechanisms. You will be responsible for embedding quality checks within CI/CD workflows, ensuring that defects are identified and addressed early in the delivery process.
The ideal candidate combines hands-on experience in data quality engineering, automation testing, ETL validation, and pipeline monitoring with strong analytical and problem-solving skills. Experience supporting AI-driven solutions, vector databases, retrieval-augmented generation (RAG) systems, and Retail Marketing Technology platforms will be highly valued. This is a hybrid position requiring regular collaboration with client and project teams to deliver high-quality outcomes in a fast-paced environment.
In This Role, You Will
- Coordination with all upstream and downstream integration partners
- Automated Testing: Design automated frameworks to check data freshness, uniqueness, and integrity across pipelines.
- Pipeline Validation: Test ETL (Extract, Transform, Load) logic to confirm transformations match business requirements.
- Data Profiling: Inspect raw data sources to uncover anomalies, missing values, or formatting inconsistencies.
- Incident Alerting: Set threshold alerts to catch bad data before it hits production reports or dashboards.
- CI/CD Integration: Embed quality checks into deployment workflows so faulty code is blocked early.
- Role should be hybrid model.
Work Model
We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 3-4 days a week in a client or Cognizant office in Deerfield, IL. Regardless of your working arrangement, we are here to support a healthy work-life balance though our various wellbeing programs.
*Please note, this role is not able to offer visa transfer or sponsorship now or in the future*
Required Qualifications
- Highly skilled Data Quality Engineer experience in testing of Proficiency in Implement validation checks, monitoring, and alerting to ensure pipeline health and data freshness for AI models and Retail Marketing technology domain experience.
- Reviewing requirements, defining test strategies, and participating in quality audits. Ensure that the team follows the testing standards, guidelines, and testing methodology as specified in the test strategy.
- Load, refresh, and maintain vector databases and document stores for retrieval-augmented generation (RAG) systems.
· Proficiency in debugging / troubleshooting skills and Experience in Co-Ordinating with cross-functional team / third party application partners.
Additional Information
We welcome applicants who share our mission and can make an impact in a variety of ways. Even if you don’t meet every listed requirement, we encourage you to apply. Consider your transferable experience and unique skills that may bring fresh perspective to the role.
Salary and Other Compensation:
Applications will be accepted until September 27th , 2026.
The annual salary for this position is between $71,100 - $112,500 depending on the experience and other qualifications of the successful candidate.
This position is also eligible for Cognizant’s discretionary annual incentive program and stock awards, based on performance and subject to the terms of Cognizant’s applicable plans.
Benefits: Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:
- Medical/Dental/Vision/Life Insurance
- Paid holidays plus Paid Time Off
- 401(k) plan and contributions
- Long-term/Short-term Disability
- Paid Parental Leave
- Employee Stock Purchase Plan
Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
About Cognizant:
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, bridging the gap between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, drive tangible outcomes and keep global enterprises ahead in a fast-changing world. See how at cognizant.ai or @cognizant.
Additional employment information
Compensation information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.
Applicants may be required to attend interviews in person or by video conference. In addition, candidates may be required to present their current state or government issued ID during each interview.
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, state or local laws.
