Senior QA Engineer / QA Lead – Data Engineering & Test Automation

SID Information Technologies; Hyderabad; Hybrid; INR 2,500,000 - 4,000,000; Full time

Job summary

SID Information Technologies seeks a Senior QA Engineer / QA Lead to drive quality across data pipelines, data warehouses, web apps, and analytics dashboards. The role combines hands-on testing with team leadership in a hybrid/on-site environment.

You will establish QA standards, build automation with Python/pytest, and execute data-quality checks across ETL/ELT and source-to-target workflows, while collaborating with data engineers to ensure release quality.

Qualifications

• 7+ years of QA experience, including 4+ years in data pipeline or data warehouse testing (ETL/ELT).
• 2+ years of experience leading or mentoring QA engineers.
• Proven experience establishing or improving QA processes, test strategies, release gates, and sign-off procedures.
• Strong Python test automation experience using pytest or similar frameworks.
• Advanced SQL skills and experience working with large datasets.
• Hands-on experience with AWS data services such as Athena, Redshift, S3, and AWS Glue.
• Experience with UI test automation using Playwright, Selenium, or equivalent tools.
• Practical experience using AI tools in testing, with the ability to validate generated code, queries, and results.
• Excellent communication, analytical, and problem-solving skills.

Responsibilities

• Lead and mentor junior QA engineers, review test plans and results, and improve team performance.
• Establish QA standards, test strategies, release gates, defect tracking, and sign-off procedures using Jira.
• Design reusable test automation frameworks using Python, pytest, and SQL.
• Validate ETL/ELT pipelines, data warehouses, and source-to-target data reconciliation.
• Perform advanced data-quality checks, including row counts, duplicate detection, joins, and data completeness.
• Test web applications and analytics dashboards using manual testing and automation tools such as Playwright or Selenium.
• Write advanced SQL queries using CTEs, window functions, and complex joins to validate data across source, staging, and delivery layers.
• Collaborate with data engineers to investigate defects and provide evidence-based go/no-go recommendations for releases.
• Verify that applicable data privacy, de-identification, and data-sharing requirements are met before data is released.

Skills

QA Leadership

QA Experience

Data Testing

Test Automation

Python testing

SQL

UI Test Automation

AWS Data Services

Data Privacy

AI Testing Tools

Tools

Playwright

Selenium

Python

PySpark

Apache Airflow

Jira

Great Expectations

Deequ

GitHub Actions

Jenkins

AWS Glue

Job description

Employment Type: Full-Time

Experience: 7+ Years

Work Mode: Hybrid / Onsite (as applicable)

We are looking for an experienced Senior QA Engineer / QA Lead to drive quality assurance across data engineering pipelines, data warehouses, web applications, and analytics dashboards. The ideal candidate will combine strong technical testing skills with team leadership, test automation expertise, and a structured approach to release quality.

Key Responsibilities

• Lead and mentor junior QA engineers, review test plans and results, and improve team performance.
• Establish QA standards, test strategies, release gates, defect tracking, and sign-off procedures using Jira.
• Design reusable test automation frameworks using Python, pytest, and SQL.
• Validate ETL/ELT pipelines, data warehouses, and source-to-target data reconciliation.
• Perform advanced data-quality checks, including row counts, duplicate detection, joins, and data completeness.
• Test web applications and analytics dashboards using manual testing and automation tools such as Playwright or Selenium.
• Write advanced SQL queries using CTEs, window functions, and complex joins to validate data across source, staging, and delivery layers.
• Collaborate with data engineers to investigate defects and provide evidence-based go/no-go recommendations for releases.
• Verify that applicable data privacy, de-identification, and data-sharing requirements are met before data is released.
  

Mandatory Skills & Qualifications:

• 7+ years of QA experience, including at least 4 years in data pipeline or data warehouse testing (ETL/ELT).
• 2+ years of experience leading or mentoring QA engineers.
• Proven experience establishing or improving QA processes, test strategies, release gates, and sign-off procedures.
• Strong Python test automation experience using pytest or similar frameworks.
• Advanced SQL skills and experience working with large datasets.
• Hands-on experience with AWS data services such as Athena, Redshift, S3, and AWS Glue.
• Experience with UI test automation using Playwright, Selenium, or equivalent tools.
• Practical experience using AI tools in testing, with the ability to validate generated code, queries, and results.
• Excellent communication, analytical, and problem-solving skills.

Preferred Skills

• Genomics or oncology data experience is a major plus — including genomic variants, biomarkers, cancer types, and treatment data.
• Healthcare data experience involving EHR, claims, laboratory data, HIPAA/PHI, or de-identification.
• Data-quality frameworks such as Great Expectations or Deequ.
• PySpark, Apache Airflow, and data pipeline orchestration.
• CI/CD tools such as GitHub Actions or Jenkins.
• Familiarity with Agile/Scrum methodologies.