Job Title:  Senior Consultant | ETL Testing | Delhi | Engineering

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).

Good to Have

• 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.

Soft Skills

• 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.