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McGraw Hill LLC.

Data Quality Assurance Engineer - IICS/Informatica

Posted 7 months ago
2-5 years experience
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AI Summary

The engineer will execute quality assurance activities for data solutions on AWS and Oracle, focusing on automated testing for ETL pipelines and analytics workflows. Responsibilities include validating and reconciling data from financial and operational systems, and collaborating with engineers to implement effective QA validation strategies.

Overview

Build the Future
At McGraw Hill, we create best-in-class, next-generation learning platforms used by millions of students and educators worldwide from kindergarten through graduate school.

We are looking for a Data Quality Assurance Engineer to join our growing technology team operating remotely from India.

How will you create an impact?
In this role, you’ll help ensure the quality, accuracy, and reliability of our data platforms and analytics solutions. You will work closely with data engineers, analysts, and business stakeholders to validate data pipelines, reporting systems, and cloud-based analytics environments. Your contributions will directly support high-quality, trusted data solutions that power critical business decisions across the organization.

What will you be doing?

  • Execute quality assurance activities for data solutions built on AWS and Oracle platforms, focusing on automated and repeatable testing approaches.
  • Design, implement, and maintain automated data quality and regression test cases for ETL pipelines and analytics workflows.
  • Validate and reconcile data from financial and operational systems, including Oracle ERP and database environments, ensuring accuracy and integrity across SCD-based data models.
  • Perform data reconciliation, performance validation, and accuracy checks across modern cloud data platforms and data lake architectures.
  • Collaborate with data engineers and analysts to understand business requirements and implement effective QA validation strategies.
  • Review data models, fact/dimension structures, star schemas, and integration logic to proactively identify and mitigate data quality risks.
  • Track, document, and manage defects using Jira while supporting QA activities within Agile or Kanban delivery environments.
  • Contribute to end-to-end QA execution across the SDLC, maintaining clear documentation and ensuring high standards of quality delivery.

 

We are looking for someone with:

  • Minimum 3+ years of hands-on experience in data quality assurance supporting data engineering or analytics solutions.
  • Strong SQL skills for data validation, reconciliation, and analysis.
  • Working knowledge of data warehousing concepts, dimensional modelling, and modern data lake architectures.
  • Hands-on experience with ETL tools such as Informatica / IICS and QA automation techniques for data validation
  • Experience with any one cloud data platforms and services including AWS (Athena with Iceberg, Lambda, EMR, Glue), Databricks, OCI, or Azure
  • Proficiency in scripting or programming languages such as Python or Scala or Java or Node.js, along with Unix/Linux shell scripting experience
  • Experience using Agile methodologies and tools such as Jira and Confluence.
  • Familiarity with APM, logging, and monitoring tools to support performance validation and issue resolution.

Why work for us?
The work you do at McGraw Hill is work that matters. You will play a key role in delivering trusted, high-quality data solutions that support the future of education. Join us and be part of a team that values innovation, collaboration, and continuous improvement while making a meaningful impact on learners and educators around the world.

 

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