Overview
Build the future!
McGraw Hill is a global education innovation company offering solutions from textbooks to cutting-edge digital platforms that improve learning outcomes. To support our growing Data & Analytics capability, we are hiring a Lead QA Automation Engineer who will play a key role in ensuring the quality and reliability of our data platforms and analytics solutions. This role will be based remotely in India.
How are you creating an impact?
As a Lead QA Automation Engineer, you will be responsible for embedding quality across McGraw Hill’s data ecosystem by designing and scaling automated testing frameworks. You will work closely with data engineers, analysts, and business stakeholders to ensure data accuracy, integrity, and reliability across pipelines and reporting systems. Your work will directly contribute to building robust, scalable, and high-performing data solutions by catching defects early and enabling data-driven decision-making across the organization.
What will you be doing?
• Execute automated QA activities for data solutions across cloud platforms with a focus on CI/CD-driven testing
• Design, develop, and maintain automated test suites for ETL pipelines and analytics solutions using tools such as pytest, Great Expectations, dbt tests, Selenium, or Playwright
• Validate data from financial and operational systems (e.g., Oracle ERP, databases), including SCD-based data models, through automated validation frameworks
• Perform automated data reconciliation, accuracy checks, and performance validation across cloud data platforms
• Collaborate with data engineers and analysts to understand requirements and implement automation-first QA strategies
• Validate data pipelines, transformations, and workflows to ensure correctness and efficiency
• Review data models (fact/dimension, star schemas) to identify data quality risks and incorporate them into automated testing coverage
• Track and manage defects using Jira while supporting QA processes in Agile/Kanban environments
• Contribute to end-to-end QA automation across the SDLC with clear documentation and scalable frameworks
We are looking for someone having:
• Bachelor’s degree in a related field or equivalent experience
• 5+ years of experience in data quality assurance with a strong focus on automation
• Hands-on experience with QA automation tools such as Selenium, Playwright, pytest, Cypress, or similar
• Strong experience in building and maintaining automated QA frameworks for ETL and data validation
• Proficiency in SQL for data validation, reconciliation, and root cause analysis
• Experience with Informatica/IICS along with Python for automation
• Solid understanding of data warehousing and modern data lake/lakehouse architectures (SCD, medallion, schema design)
• Hands-on experience with AWS (Athena, Glue, EMR, Lambda) and Databricks
• Experience integrating automated test suites into CI/CD pipelines (Jenkins, GitHub Actions, Azure DevOps)
• Working knowledge of scripting languages such as Python, Scala, Java, or Node.js
• Familiarity with Unix/Linux scripting
• Strong problem-solving skills and ability to work in Agile environments
Nice to have:
• Experience in EdTech or publishing domain
• Familiarity with BI tools such as Power BI, Tableau, or Alteryx
Why work with us?
There has never been a better time to join McGraw Hill. In our culture of curiosity, collaboration, and innovation, you’ll have the opportunity to work on impactful data initiatives, build scalable quality frameworks, and contribute to shaping the future of learning.
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