QA Engineer – ETL & Data Warehouse Testing

Location: Pune / Hybrid

Experience: 4–7 Years

Relevant Experience: 3+ Years in ETL / Data Warehouse Testing

Industry Preference: SaaS / Product Engineering

Availability: Immediate Joiners Preferred

Role Overview

We are looking for a QA Engineer with solid ETL and Data Warehouse testing experience to ensure data quality across source systems, staging, transformation, warehouse, and reporting layers.

The role involves SQL-based data validation, ETL testing, data reconciliation, automation, and BI/report validation, working closely with Data Engineers, BI Developers, and Business Analysts.

Key Responsibilities

- Review requirements, source-to-target mappings, and data models to identify test scenarios.
- Create test strategies, test plans, test cases, and traceability matrices.
- Perform ETL/DWH testing across source, staging, ODS, data warehouse, and data mart layers.
- Write complex SQL queries using joins, CTEs, subqueries, aggregations, and window functions.
- Perform data completeness, accuracy, integrity, duplicate, null, and reconciliation checks.
- Validate transformation logic, business rules, lookups, and derived columns.
- Test Fact/Dimension tables and SCD Type 1, 2 & 3.
- Validate full, incremental, Delta/CDC loads, error handling, restartability, and reject logic.
- Validate ETL scheduling, dependencies, performance, and SLA adherence.
- Validate BI reports and dashboards against warehouse data.
- Build automated data validation scripts and integrate them with CI/CD.
- Track defects in Jira, perform retesting, and support root-cause analysis.
- Participate in Agile ceremonies and mentor junior QA members.Required Skills

- Required Skills




- 4–7 years of QA experience with 3+ years in ETL / Data Warehouse Testing.
- Strong SQL skills with Oracle, SQL Server, PostgreSQL, MySQL, or Teradata.
- Solid understanding of Data Warehousing, Star/Snowflake Schema, OLTP vs OLAP, Facts, Dimensions, and SCDs.
- Hands-on experience with ETL tools such as Informatica, SSIS, Talend, DataStage, or Azure Data Factory.
- Experience with cloud data platforms such as Snowflake, Redshift, BigQuery, Synapse, or Databricks.
- Ability to interpret source-to-target mappings and create test cases.
- Scripting knowledge in Python or Shell for automation/data comparison.
- Experience testing CSV, JSON, XML, Parquet, and other data sources.
- Good knowledge of STLC, defect lifecycle, and Agile/Scrum.
- Experience with Jira and test management tools such as Zephyr, Xray, TestRail, or qTest.

- Good to Have
- Great Expectations, dbt Tests, Soda, or QuerySurge.
- Python libraries such as Pandas/PySpark and Pytest.
- Big Data technologies: Spark, Hive, Kafka, Airflow.
- CI/CD: Jenkins, GitHub Actions, Azure DevOps.
- BI testing with Power BI, Tableau, Qlik, or Looker.
- Data governance, lineage, masking, GDPR/PII knowledge.
- API testing using Postman or REST Assured.
- BFSI, Healthcare, Retail, or Telecom domain experience.
- Key Technical Stack
- SQL: Oracle, SQL Server, PostgreSQL, Teradata
- Cloud DWH: Snowflake, Redshift, BigQuery, Synapse, Databricks
- ETL/ELT: Informatica, SSIS, Talend, ADF, AWS Glue, dbt
- Automation: Python, Pytest, Great Expectations, QuerySurge
- Orchestration: Airflow, Control-M, Autosys
- BI: Power BI, Tableau
- Test Management: Jira, Zephyr/Xray, TestRail
- CI/CD: Git, Jenkins, Azure DevOps

📌 QA Engineer (ETL & Data Warehouse Testing) (India)
🏢 Recrui8
📍 India