Senior Quality Engineer

Optum; Chennai District; Hybrid; INR 1,200,000 - 2,400,000; Full time

Job summary

Optum is seeking a Senior ETL QA Tester to ensure data accuracy, completeness, and performance of enterprise pipelines. The role emphasizes AI-assisted quality engineering and cloud testing across AWS/Azure.

The candidate will design test strategies, execute end-to-end testing, and collaborate with data engineers, analysts, and product owners to improve data quality and test efficiency.

Qualifications

• Graduate degree or equivalent experience.
• 6+ years of ETL/Data Warehouse Testing experience.
• Experience with Agile/Scrum and Jira/Rally.
• Strong SQL and ETL tool expertise.

Responsibilities

• ETL/Data validation across source, staging, and target systems.
• Validate data pipelines in cloud environments such as Azure, AWS.
• Develop test strategies, plans, and cases for ETL and data warehouse projects.
• Identify, document, and retest defects with cross-functional teams.
• Leverage AI-powered testing tools to optimize test cases and coverage.
• Automate ETL validation via Python, SQL, and CI/CD integration.

Skills

Advanced SQL

ETL testing

Data warehousing

Cloud testing (AWS/Azure)

Databricks

Python

Test automation

AI-assisted testing

Education

Graduate degree or equivalent experience

Tools

Databricks

AWS

S3/Redshift

Great Expectations

PyTest

Selenium

Cypress

GitHub Copilot

ChatGPT QA

Postman

Job description

We are seeking an experienced Senior ETL QA Tester with expertise in data warehouse testing, ETL validation, cloud-based data platforms, and AI-assisted quality engineering practices. The ideal candidate will be responsible for ensuring the accuracy, completeness, integrity, and performance of enterprise data pipelines. This role leverages AI-powered testing tools to improve test coverage, accelerate defect detection, optimize test case generation, and enhance overall testing efficiency.

Primary Responsibilities:

• ETL & Data Validation
  • Validate ETL/ELT processes across source, staging, and target systems
  • Perform data reconciliation, data quality, and data integrity testing
  • Create and execute SQL queries to validate complex data transformations
  • Verify business rules, data mappings, and transformation logic
  • Analyze source-to-target mapping documents and data lineage
  • Validate data migration and conversion activities
• Validate data pipelines in cloud environments such as Azure, AWS
  • Perform testing on large-scale datasets using AWS Redshift, Databricks
• Test Planning & Execution
  • Develop comprehensive test strategies, test plans, and test cases for ETL and data warehouse projects
  • Perform functional, integration, regression, system, and end-to-end testing
  • Execute batch process validation and workflow testing
  • Conduct negative testing and boundary condition validation
  • Review requirements and identify test scenarios with minimal ambiguity
• Identify, document, track, and retest defects
  • Collaborate with developers, data engineers, business analysts, and product owners to resolve issues
  • Conduct root cause analysis and recommend process improvements
• AI-Assisted Quality Engineering
  • Utilize AI-powered testing tools to generate and optimize test cases
  • Leverage AI assistants for SQL generation, test data creation, defect analysis, and root cause identification
  • Use AI-based anomaly detection techniques to identify data quality issues
  • Apply predictive analytics to prioritize testing efforts and identify high-risk areas
  • Automate repetitive validation tasks using AI-driven frameworks
• Automation & Continuous Testing
  • Design and maintain automated ETL validation frameworks
  • Develop automated test scripts using Python, SQL, or other automation tools
  • ntegrate automated testing into CI/CD pipelines
  • Monitor and analyze test execution reports and quality metrics
• Leadership & Collaboration
  • Mentor junior QA engineers and provide technical guidance
  • Participate in Agile ceremonies including sprint planning, daily standups, and retrospectives
  • Drive quality best practices across projects
  • Review peer test artifacts and automation code
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regard to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Qualifications - External

Required Qualifications:

• Graduate degree or equivalent experience
• 6+ years of ETL/Data Warehouse Testing experience
• Solid experience testing enterprise data warehouse applications
• Experience working in Agile/Scrum environments and tools such as Jira/Rally
• Technical Skills
  • Advanced SQL skills with experience in complex joins, stored procedures, functions, and performance tuning
  • Hands-on knowledge of ETL tools
  • Cloud Testing - AWS Services - S3, Redshift, Data pipelines, Step function, EC2, etc.
  • Databricks
  • Automation
    • Python
    • PyTest
    • Great Expectations Framework
    • SQL-based automation frameworks
    • Selenium/Cypress - Good to know
  • AI Tools
    • Microsoft Copilot
    • GitHub Copilot
    • ChatGPT - Prompt Engineering
    • AI-powered test automation platforms
    • AI-based data validation and anomaly detection tools

Preferred Qualifications:

• Certifications:
  • Microsoft Azure Data Engineer Associate
  • Microsoft Azure Fundamentals
  • ISTQB Advanced Test Analyst
  • Certified Agile Tester
  • Snowflake Certification
  • Databricks Data Engineer Certification
• Healthcare domain experience
• Experience with Data Lake and Big Data testing
• Experience with API testing using Postman or Rest Assured
• Familiarity with ML/AI data validation testing
• Knowledge of Data Governance and Data Quality frameworks