Data Warehouse Testing

Responsibilities and JD in brief along with additional criteria to be considered (if any):

• Hands-on experience in ETL Testing, Data Warehouse Testing, and Data Migration Testing.
• Strong expertise in SparkSQL and database validation across Oracle, SQL Server, PostgreSQL, Snowflake, AWS Redshift, or BigQuery.
• Validate source-to-target mappings, transformation rules, data lineage, and business logic as per mapping documents.
• Experience in Python-based ETL test automation.
• Perform data reconciliation, completeness checks, referential integrity, duplicate detection, and data quality validations.
• Experience in ETL tools such as Informatica, Ab Initio, ODI, SSIS, DataStage, Azure Data Factory, or Databricks.
• Strong understanding of Data Warehousing concepts including Facts, Dimensions, Star Schema, and SCD validations.
• Experience designing and implementing Spark-based Data Validation frameworks to validate large-scale financial data across batch and ETL pipelines, ensuring data quality, completeness, accuracy, and consistency throughout the project lifecycle.
• Experience developing automated data quality controls and validation test suites using Apache Spark, including reconciliation, schema validation, data profiling, and exception handling for high-volume financial datasets
• Experience validating cloud-based data platforms on AWS, Azure, Databricks, Snowflake, or GCP.
• Hands-on experience with batch job validation, workflow monitoring, and scheduling tools such as Autosys, Control-M, or Airflow.
• Develop automation solutions using Python/Shell scripting for ETL and data validation activities.
• Implement test strategies, prepare and execute test cases, analyze results, and coordinate defect resolution to ensure data quality.
• Collaborate with business, development, and data engineering teams to ensure accurate and reliable data delivery.
• Maintain detailed documentation of test scenarios, SQL validations, automation assets, and testing processes.

Nice to Have Skills:

• Experience in BI Reporting validation using Power BI, Tableau, Qlik, or MicroStrategy.
• Experience in Big Data technologies such as Hadoop, Spark, Hive, and Kafka.
• Knowledge of AI-enabled Data Quality and Data Governance solutions.
• Banking, Capital Markets, Wealth Management, or Mortgage domain experience.