What makes Cognizant a unique place to work? The combination of rapid growth and an international and innovative environment! This is creating many opportunities for people like YOU — people with an entrepreneurial spirit who want to make a difference in this world.
At Cognizant, together with your colleagues from all around the world, you will collaborate on creating solutions for the world's leading companies and help them become more flexible, more innovative, and successful. Moreover, this is your chance to be part of the success story.
Position Summary:
The Lead Data QA Automation Engineer / QA Architect will be responsible for leading data quality assurance, ETL testing, and automated validation initiatives across large-scale cloud data migration and transformation programs.
The role requires deep expertise in data validation, test automation, data profiling, reconciliation, and governance across complex enterprise data platforms.
The Lead Data QA Automation Engineer / QA Architect will design and implement reusable automation frameworks using SQL, Data Build Tool (DBT), Python, and PySpark, ensuring data integrity across batch and real-time ingestion pipelines spanning APIs, SAP, legacy platforms, and cloud-native ecosystems such as Azure and Databricks.
This position will support business-critical programs within insurance, banking, financial services, life sciences, and related domains, with a strong focus on regulatory compliance, stakeholder collaboration, and delivery excellence.
Key Skills and Technical Competencies
1.Advanced ETL testing, data validation, data reconciliation, and enterprise-scale data migration assurance specifically in the Australian Insurance domain
2.Experience with design, build, and maintaining scalable data QA automation frameworks through DBT is mandatory
3.Capability to leverage GitHub Co-pilot for Test Cases drafting from Source To Target mappings
4.Experience in leading stakeholder management, cross-functional collaboration, and global delivery coordination across distributed teams
5.Experience in periodical stakeholder reports preparation through automated Jira dashboards using Atlassian Rovo
6.Experience in delivering business continuity for customer applications by stitching and producing independent data objects, specifically integrating Duck Creek policy information with existing customer data.
7.Strong hands-on expertise in SQL, Python, and PySpark for automated data quality validation and test execution
8.Experience with cloud data platforms including but not limited to Azure Data Factory, Azure Data Lake Storage Gen2, Azure Synapse, Databricks, Delta Lake, and GCP-trained environments
9.Proficiency with ETL and data integration tools such as Informatica PowerCenter, Informatica IICS, Talend, SAP BODS, and Azure Data Factory
10.Strong understanding of data warehouse, lakehouse, and Delta Lake validation across Bronze, Silver, and Gold architecture layers
11.Knowledge of GxP compliance, regulatory data validation, audit readiness, and controlled validation processes
12.Experience validating batch, near-real-time, and API-driven data pipelines involving SAP and enterprise source systems
13.Strong working knowledge of Agile/Scrum delivery, SDLC, test strategy, traceability matrices, and defect lifecycle management
14.Effective stakeholder management, cross-functional collaboration, and global delivery coordination across distributed teams
Roles and Responsibilities
1.Lead end-to-end data testing and validation delivery for insurance, banking, financial services, and enterprise transformation programs
2.Define, design, and implement scalable ETL and data QA automation frameworks using
3.Validate complex data migrations from legacy platforms to cloud environments while ensuring accuracy, completeness, and consistency
4.Perform source-to-target validation across policy, claims, customer, billing, financial, and operational datasets
5.Ensure data quality across batch and real-time ingestion pipelines involving APIs, SAP, and other enterprise source systems
6.Establish test strategy, governance models, compliance controls, and validation approaches aligned with business and regulatory requirements
7.Collaborate with data engineers, architects, product owners, business stakeholders, and delivery teams to drive successful outcomes
8.Conduct data profiling, reconciliation, exception analysis, and root cause investigation to support defect prevention and remediation
9.Drive risk mitigation, quality improvement, reusable asset development, and continuous improvement initiatives across delivery engagements
10.Provide clear delivery reporting, stakeholder communication, quality metrics, and progress updates to leadership teams
Domain Experience
1.Insurance (mandatory): Policy administration, claims processing, underwriting, billing, and large-scale data migration across platforms such as Redshift, Databricks, Data Build Tool (DBT) and Duck Creek-type ecosystems
2.Banking and Financial Services: Regulatory reporting, IFRS15, risk and compliance, financial data warehousing, and enterprise reporting platforms
3.Life Sciences: GxP compliance, clinical data validation, regulatory data controls, and validated reporting environments
4.Energy and Utilities: Large-scale data migration, analytics modernization, and enterprise data platform validation
5.Retail: Customer, supply chain, transaction, and operational data validation across business-critical systems
Total experience
1.15+ years
Education and Certifications
- Bachelor of Engineering in Electronics and Telecommunications
- CDAC Certification
Salary Range: >$100,000
Date of Posting: 19-Aug-26
Next Steps: If you feel this opportunity suits you, or Cognizant is the type of organization you would like to join, we want to have a conversation with you! Please apply directly with us.
For a complete list of open opportunities with Cognizant, visit http://www.cognizant.com/careers. Cognizant is committed to providing Equal Employment Opportunities. Successful candidates will be required to undergo a background check.
