ETL Test Engineer

4 days ago

Gurgaon, Haryana, India Capgemini Full time ₹ 6,00,000 - ₹ 18,00,000 per year

Role & responsibilities

Role Overview

  • We are looking for an experienced Software Development Engineer in Test (SDET) with strong expertise in ETL testing, database validation, and Python-based automation.
  • The ideal candidate will ensure data integrity and accuracy across ETL pipelines and data warehouse systems, while leveraging deep technical and analytical skills.
  • Exposure to the banking domainespecially Corporate & Institutional Banking and Personal Bankingwill be a strong advantage.

Key Responsibilities


• Design and develop Python-based automation frameworks and reusable utilities for ETL validation and data reconciliation.


• Conduct end-to-end ETL testing, including source-to-target validation, transformation logic verification, and data completeness checks.


• Write, review, and optimize SQL queries (joins, CTEs, window functions) to validate complex business rules and data transformations.


• Execute Unix/Linux commands and shell scripts for ETL job monitoring, file validation, and log analysis.


• Work with Mainframe systems for flat file validation, dataset checks, and job executions in ETL processes.


• Test data warehouse components such as staging, fact, and dimension tables, including Slowly Changing Dimensions (SCDs).


• Integrate automated validation into ETL CI/CD pipelines (Jenkins, GitHub Actions).


• Collaborate with ETL developers, data modelers, and business analysts to investigate issues and ensure accurate data flow across banking systems.


• Prepare test evidence, automation reports, and dashboards for traceability and coverage metrics.

Must Have


• Strong proficiency in Python (pandas, pyodbc, data comparison and validation frameworks).


• Expertise in SQL — complex joins, aggregations, subqueries, and analytical functions.


• Strong understanding of Oracle databases/datawarehouse and relational data modeling.


• Proficiency in Unix/Linux commands (grep, awk, sed, shell scripting).


• Basic knowledge of Mainframe systems for dataset handling.


• Good understanding of Data Warehousing concepts — staging, data marts, fact/dimension modeling, and SCD handling.


• Familiarity with test management tools (Rally, JIRA, Qtest) and CI/CD tools (Git, Jenkins).

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