Key skills
SAS programmingDATA StepPROC SQLSAS macrosSAS datasetsSAS job analysisPythonPySparkETL validationSource-to-target testingData quality validationData reconciliationAdvanced SQLDefect analysisRoot cause investigationStakeholder managementSQLETLSnowflakeDatabricksAgileStakeholder ManagementCommunication
About this role
Cognizant is a leading digital company, and they are seeking a SAS Data Engineer to support large-scale SAS migration and modernization initiatives. The role involves collaborating with various teams to ensure successful migration outcomes through data validation, quality assurance, and automation.
Responsibilities:
- Analyze SAS programs, jobs, datasets, and business logic to support migration, modernization, and validation activities
- Design and execute test scenarios to validate migrated solutions and ensure functional equivalency between source and target platforms
- Perform data reconciliation and source-to-target validation to ensure data accuracy, completeness, and quality
- Leverage Python and PySpark to automate testing, profiling, validation, and comparison processes across large datasets
- Investigate defects, perform root cause analysis, and collaborate with cross-functional teams to resolve data discrepancies
Requirements:
- 7+ years of hands-on SAS programming experience, including DATA Step, PROC SQL, macros, datasets, and job analysis
- Strong experience with Python and PySpark for data processing, automation, validation, and reconciliation activities
- Proven experience supporting SAS migration, modernization, or transformation initiatives
- Strong QA and testing expertise, including ETL validation, source-to-target testing, data quality validation, and reconciliation
- Advanced SQL skills with experience querying, profiling, and validating large datasets
- Experience performing defect analysis, root cause investigations, and documenting testing outcomes
- Strong communication and stakeholder management skills, with the ability to collaborate effectively across technical and business teams
- Experience migrating SAS workloads to modern data platforms using Python, PySpark, or cloud-based technologies
- Exposure to Databricks and/or Snowflake environments
- Experience validating ETL workflows, batch processing systems, and reporting solutions
- Knowledge of Agile delivery methodologies, test management platforms, and defect tracking tools
- Experience creating QA sign-off documentation, validation reports, and audit-ready testing artifacts