AWS Lakehouse Data Quality Assurance Testing Lead
About the role
As an AWS Lakehouse Data Quality Assurance Testing Lead, you will make an impact by driving data quality, integrity, and reliability across enterprise-scale AWS Lakehouse platforms. You will be a valued member of the Data & Analytics team and work collaboratively with data engineers, architects, business stakeholders, and quality engineering teams to ensure the successful delivery of high-quality, trusted data products that support critical business decisions.
In this role, you will:
- Lead end-to-end data quality assurance and validation activities across AWS Lakehouse environments, ensuring accuracy, completeness, consistency, and reliability of enterprise data assets.
- Design and implement scalable testing frameworks, automation strategies, and quality controls for ETL/ELT pipelines, data transformations, and analytical workloads.
- Validate data movement and processing across bronze, silver, and gold layers, ensuring compliance with established data governance and quality standards.
- Partner with cross-functional teams to identify, troubleshoot, and resolve data quality issues while driving continuous process improvements.
- Provide technical leadership and mentorship to quality engineering teams, promoting best practices in data testing, automation, and cloud-native quality assurance.
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 days per week in a Cognizant or client office in Atlanta, GA. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.
The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.
What you need to have to be considered
- 10+ years of experience in data warehousing, data engineering, data quality assurance, or data platform testing.
- Strong experience validating cloud-based data platforms, data lakes, data warehouses, and modern Lakehouse architectures.
- Hands-on expertise with SQL and Python for data validation, reconciliation, test automation, and quality assurance activities.
- Experience testing ETL/ELT pipelines, data transformations, metadata, data lineage, schema evolution, and large-scale analytical datasets.
- Knowledge of AWS data services, including Amazon S3, AWS Glue, Amazon Athena, and related cloud-native data technologies.
- Experience implementing data quality frameworks and automated testing solutions within enterprise environments.
- Strong understanding of data governance, data quality standards, regulatory compliance, and audit requirements.
- Excellent problem-solving, stakeholder management, communication, and leadership skills.
These will help you stand out
- Experience working with Apache Iceberg tables, Snowflake, DBT, Spark, and Airflow in large-scale data ecosystems.
- Knowledge of CI/CD practices and automated quality assurance within cloud-native delivery pipelines.
- Experience supporting enterprise data lake, data warehouse, or analytics modernization initiatives.
- Familiarity with performance testing, workload optimization, and data platform scalability assessments.
- Experience leading distributed teams and managing data quality programs across multiple delivery workstreams.
- Knowledge of Agile delivery methodologies, including Scrum, Kanban, and DevOps-based operating models.
We're excited to meet people who share our mission and can make an impact in a variety of ways. Don't hesitate to apply, even if you only meet the minimum requirements listed. Think about your transferable experiences and unique skills that make you stand out as someone who can bring new and exciting things to this role.
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.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.
