About the job

Job Description:

• Strong SQL (Complex Joins, CTEs, Window Functions, Stored Procedures, Data Validation)
• Data Warehousing Concepts
• ETL Testing & Data Migration Testing
• Data Quality & Data Reconciliation Testing
• Unix/Linux Commands
• Hadoop/Hive/HDFS
• Cloud Data Validation (GCP/AWS)
• BI Reporting Validation (Power BI / Tableau / QlikView)
• Strong expertise in SQL (Joins, Subqueries, CTEs, Window Functions, Aggregations, Stored Procedures, Data Validation).
• Strong understanding of Data Warehousing concepts (Facts, Dimensions, SCD Type 1 & Type 2, Star Schema, Snowflake Schema).
• Hands-on experience in ETL Testing, Data Migration Testing, Data Reconciliation, and Data Quality Testing.
• Good understanding of Source-to-Target Mapping (STTM) validation.
• Experience with Unix/Linux commands and shell basics.
• Hands-on experience with Hadoop ecosystem (Hive, HDFS).
• Exposure to Cloud Data Platforms: GCP: BigQuery, GCS, AWS: S3, Athena, Redshift
• Knowledge of Teradata, Oracle, SQL Server, or similar enterprise databases.
• Experience validating Power BI, Tableau, or QlikView reports and dashboards.
• Experience with defect management tools such as JIRA and Agile methodologies.

Responsibility:

• Perform ETL Testing, Data Warehouse Testing, Data Migration Testing, and Data Validation.
• Validate Source-to-Target Mapping (STTM) documents and transformation rules.
• Execute data reconciliation, completeness, accuracy, consistency, and integrity checks across multiple source and target systems.
• Validate data pipelines across Hadoop, Hive, HDFS, GCP (BigQuery, GCS), and AWS (S3, Athena, Redshift).
• Perform backend data validation using complex SQL queries.
• Validate files and datasets across Unix/Linux, HDFS, GCS, S3, and relational databases.
• Perform BI dashboard and report validation using Power BI, Tableau, or QlikView.
• Execute Data Quality Testing, identify data anomalies, duplicates, missing records, and transformation issues.
• Analyze defects, perform Root Cause Analysis (RCA), and coordinate with Data Engineering teams for resolution.
• Participate in Agile ceremonies, sprint planning, backlog grooming, and release validation.