Warehouse QA Engineer Mumbai Mumbai 2-5 Yrs

Designation : Warehouse QA Engineer

Requirements

Key Responsibilities

• Perform Data Warehouse testing for ETL/ELT workflows data transformations and downstream reporting layers.
  
• Validate data accuracy using SQL-based testing including:
  
• Row count checks
  
• Duplicate checks
  
• Null checks
  
• Referential integrity checks
  
• Aggregation validation (GROUP BY / HAVING)
  
• Join validations (INNER/LEFT joins)
  
• Perform end-to-end validation of datasets across source staging target layers.
  
• Ensure correct handling of set operations (UNION / UNION ALL / INTERSECT / EXCEPT) and business logic validation.
  
• Test and validate datasets built on Delta Tables (Delta Lake) including versioning/time-travel scenarios wherever applicable.
  
• Support QA activities in Databricks including cluster execution notebook validations and data checks.
  
• Identify and document defects with clear data proof (SQL outputs mismatch evidence).
  
• Collaborate with Data Engineers Analysts and Business stakeholders to understand requirements and define test scenarios.
  
• Maintain and improve test cases test data and validation frameworks for warehouse quality checks.
  

Required Skills (Must Have)

SQL (Strong)

• Strong hands-on SQL skills including:
  
• Joins (INNER LEFT)
  
• GROUP BY / HAVING
  
• Aggregates (COUNT SUM AVG etc.)
  
• Duplicate identification & removal logic
  
• Subqueries
  
• Understanding of UNION vs UNION ALL
  
• Set operations like INTERSECT / EXCEPT (MINUS)
  

Data Warehousing / QA

• Strong understanding of data QA fundamentals:
  
• Data reconciliation
  
• Data consistency checks
  
• Data completeness validation
  
• Schema and transformation validation
  
• Knowledge of warehouse concepts such as Fact/Dimension staging layers and reporting layers is a plus.
  

Databricks

• Practical understanding of:
  
• Databricks notebooks
  
• Cluster concept
  
• Running queries and validations inside Databricks
  

Delta Lake / Delta Tables

• Understanding of Delta Tables and their advantages such as:
  
• ACID support
  
• Versioning / Time travel
  
• Merge/upsert concepts (high-level awareness)
  

Good to Have Skills

• Basic Python knowledge for QA scripting/automation:
  
• type() usage
  
• Lists
  
• Basic coding & logic
  
• Exposure to automation frameworks for data QA (optional)
  
• Familiarity with CI/CD for data jobs (optional)
  
• Experience with tools like Jira Confluence or test management tools
  

Experience & Qualification

• 26 years experience in Data Warehouse Testing / ETL Testing / Data QA
  
• Bachelors degree in Computer Science / IT / Engineering or equivalent practical experience.
  
• Experience working with any of these databases is a plus:
  
• Oracle
  
• PostgreSQL
  
• MSSQL
  

Benefits