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Requirements and responsibilities
About The RoleIn this role, you will be responsible for building and maintaining automated data validation to ensure consistency and accuracy across cloud migration environments. You will own the validation of data integrity across processing layers, storage systems, and orchestration workflows to guarantee reliable outcomes. You will integrate quality checks into automated pipelines and produce evidence to support migration readiness and sign-off.ResponsibilitiesDesign and implement automated data validation pipelines comparing AWS and GCP outputs using Python and DatabricksDevelop and maintain data parity checks across ETL processing layersValidate message integrity across Kafka clusters and downstream processing stagesExecute object parity, replication-lag, and stored-procedure validation for migrated data storesValidate DAG execution, scheduling, retry logic, and alerting parity following Cloud Composer and Airflow migrationVerify pipeline telemetry and data-quality alerting as operational readiness evidenceCreate automated data quality gates integrated into Jenkins CI pipelinesAdopt AI-assisted and agentic workflows for validation, test authoring, and defect analysisRequirements4+ years of experience in data quality engineering, automated validation, and reconciliation across distributed systemsStrong Python skills for building data validation frameworks and automated quality checksHands-on experience with Databricks and advanced SQL for data comparison, validation, and analysisExperience validating data integrity across Kafka, Redis, and cloud-based storage platforms (e.g., S3, GCS)Knowledge of replication validation, stored-procedure parity testing, and cloud database migration quality assuranceExperience with CI/CD practices and test orchestration using Jenkins or similar toolsStrong analytical mindset with the ability to identify and troubleshoot data discrepancies across complex data pipelinesExcellent communication skills and experience collaborating with English-speaking engineering teams, leveraging modern AI-assisted development and automation tools
Optionally, you can add more information later (benefits, pre-screening questions, etc.)