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Quality Engineering Lead - ETL Testing & Automation

Accenture India Private Limited · Gurugram

📅 15/08/2026
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Quality Engineering Lead Project Role : Quality Engineering Lead Project Role Description : Leads a team of quality engineers through multi-disciplinary team planning and ecosystem integration to accelerate delivery and drive quality across the application lifecycle. Applies business and functional knowledge to develop end-to-end testing strategies through the use of quality processes and methodologies. Applies testing methodologies, principles and processes to define and implement key metrics to manage and assess the testing process including test execution and defect resolution. Must have skills : Data Warehouse ETL Testing, Python (Programming Language), Microsoft SQL Server Good to have skills : Automated Testing, Microsoft SDET Minimum 5 year(s) of experience is required Educational Qualification : 15 years full time education Summary: - 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 banking domain, especially Corporate & Institutional Banking and Personal Banking, will be a strong advantage. Roles & 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 Professional & Technical Skills: - Must To Have Skills: Proficiency in Data Warehouse ETL Testing, Python (Programming Language), Microsoft SQL Server. - Good To Have Skills: Experience with Automated Testing. - Strong understanding of data warehousing concepts and ETL processes. - 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/data warehouse 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). Good to have skill - Banking domain exposure, especially in: - Corporate & Institutional Banking (e.g., treasury, lending, payments, trade finance). - Personal Banking (e.g., retail accounts, loans, deposits, credit cards). - Knowledge of data governance and quality frameworks. - Exposure to API testing for data ingestion and integration layers. - Ability to implement data validation automation within ETL CI/CD pipelines Additional Information: - The candidate should have minimum 6 years of experience in Data Warehouse ETL Testing. - This position is based at our Gurugram Client office and it is mandate to work from client location 3 days/week. - Strong analytical and problem-solving skills with keen attention to data accuracy. - Excellent communication and collaboration with cross-functional teams. - Ability to work independently in fast-paced Agile environments. - Detail-oriented, proactive, and quality-driven mindset. - A 15 years full time education is required. .
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