Job Overview :

We are looking for a skilled ETL Tester with hands-on experience in data validation, ETL/ELT testing, SQL, and Python automation. The ideal candidate should have strong knowledge of data warehousing concepts, ETL architecture, and automated testing frameworks for validating large-scale data pipelines.

The role requires working closely with data engineers, developers, and business teams to ensure the accuracy, quality, and integrity of data across the data platform.

Mandatory Skills :

ETL / ELT Testing :

- Hands-on experience in S2T reconciliation, transformation validation, and data reconciliation.

- Experience designing regression strategies for data pipelines.

Advanced SQL :

- Expertise in joins, CTEs, window functions, and aggregations.

- Ability to write performance-optimized queries for large datasets.

Python Automation :

- Strong experience with Python automation and Pytest.

- Ability to build and maintain automated data validation test suites.

- ETL Architecture & Data Warehouse Concepts

- Strong understanding of ETL/ELT data flows.

- Knowledge of staging, ODS, and data warehouse architecture.

- Understanding of data quality dimensions.

Test Management :

- Experience using Jira and/or X-Ray for test management and defect tracking.

- Agile Methodology

- Experience working in Agile/Scrum development environments.

Must-Have Technical Skills :

- Strong Unix/Linux command knowledge for log validation, job monitoring, and troubleshooting.

- Strong Python fundamentals including :

- Data structures (lists, tuples, sets, dictionaries)

- Object-Oriented Programming

- File handling and debugging

- Database connectivity

- Experience with Pandas / DataFrames and lambda functions for data transformations and checks.

- Basic exposure to cloud environments (AWS preferred).

- Experience with Boto3 is an added advantage.

- Strong communication and documentation skills to explain data issues to both technical and business teams.

Good to Have Skills :

- Understanding of Databricks and PySpark, especially for testing Lakehouse architectures.

- Experience with cloud data platforms such as:

- Snowflake

- Databricks

- BigQuery

- Redshift

- Synapse

- Experience with RDBMS such as PostgreSQL, SQL Server, or Oracle.

- ETL / ELT Tools

- Informatica

- DataStage

- SSIS

- Talend

- dbt

- Airflow

- Data Quality Tools

- Great Expectations

- Deequ

- Knowledge of metadata and data lineage concepts.

- CI/CD & Reporting

- Allure

- JUnit XML

- Environment and release management

- API Testing

- Postman

- REST API validation for data services

Key Responsibilities :

- Perform hands-on ETL/ELT testing including S2T reconciliation, transformation validation, and data reconciliation.

- Design and execute regression testing strategies for data pipelines.

- Write and optimize complex SQL queries (joins, CTEs, window functions, aggregations) for large datasets.

- Develop and maintain automation scripts using Python and Pytest for data validation.

- Validate ETL workflows and data warehouse layers including staging, ODS, and warehouse environments.

- Track and manage defects using Jira or X-Ray, ensuring proper documentation and closure.

- Work in Agile/Scrum environments supporting sprint activities and story-level testing.

- Collaborate with developers and data engineers to identify and resolve data quality issues.

- Document test results and provide insights on data discrepancies and system behavior.