QA Engineer - Databricks

Moody's Analytics; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Moody's Analytics is seeking a Data Quality Engineer to ensure data quality across large Databricks pipelines. You will design and implement automated validation for Bronze, Silver, and Gold data layers, using Databricks SQL, PySpark, and Python to build scalable testing frameworks.

Collaborate with engineering and product teams to enforce data quality and release readiness. The role requires 4+ years in QA/Data Quality within enterprise data platforms, experience with Agile/Scrum, and strong

Qualifications

• 4+ years of experience in Software Quality Assurance or Data Quality Engineering within large-scale enterprise data platforms.
• Strong hands-on experience with Databricks SQL and Python, including testing of notebooks, workflows, and scheduled jobs.
• Solid understanding of Medallion architecture (Bronze, Silver, Gold) and data lifecycle validation practices.
• Expertise in PySpark for data validation, test automation, and building scalable testing frameworks.
• Strong proficiency in SQL and data validation techniques across dataset, record, schema, and transformation levels.
• Experience designing integration, end to end, and regression testing strategies with an automation first mindset.
• Experience working in Agile or Scrum environments with tools such as Xray for test management and Jira for defect tracking.
• Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges.

Responsibilities

• Ensure data quality, reliability, and correctness across large scale Databricks batch pipelines through automated validation and testing practices.
• Own end to end data quality validation for Databricks pipelines across Bronze, Silver, and Gold layers.
• Validate data completeness, accuracy, consistency, timeliness, and business rule correctness using Databricks SQL and Delta tables.
• Perform dataset, record, schema, and transformation level validations including source to target mapping and derived field checks.
• Design, develop, and maintain reusable and scalable data validation frameworks using PySpark and Python on Databricks.
• Automate integration, regression, and end to end testing for notebooks, workflows, and scheduled jobs.
• Define and implement test data management strategies including data refresh, masking, and environment isolation.
• Manage test cases, execution, and defect tracking using Xray and Jira while maintaining test documentation and validation evidence.
• Collaborate with engineering, platform, and product teams to enforce data quality standards and communicate risks and release readiness.

Skills

Databricks SQL

Python

PySpark

SQL

Data validation

Agile/Scrum

AI concepts

Education

Bachelor's degree in Computer Science / IT / Engineering

Tools

Databricks

PySpark

Xray

Jira

Delta Lake

Job description

Job Summary

At Moodys, we unite the brightest minds to turn today s risks into tomorrow s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are-with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we re advancing AI to move from insight to action-enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

Skills and Competencies

• 4+ years of experience in Software Quality Assurance or Data Quality Engineering within large-scale enterprise data platforms
• Strong hands-on experience with Databricks SQL and Python, including testing of notebooks, workflows, and scheduled jobs
• Solid understanding of Medallion architecture (Bronze, Silver, Gold) and data lifecycle validation practices
• Expertise in PySpark for data validation, test automation, and building scalable testing frameworks
• Strong proficiency in SQL and data validation techniques across dataset, record, schema, and transformation levels
• Experience designing integration, end to end, and regression testing strategies with an automation first mindset
• Experience working in Agile or Scrum environments with tools such as Xray for test management and Jira for defect tracking
• Demonstrated proficiency in artificial intelligence concepts, with hands-on experience using AI tools to streamline workflows and enhance operational efficiency. Proven ability to implement AI-powered solutions to solve business challenges. Demonstrates a growing awareness of AI risk management and a commitment to responsible and ethical AI use.

Education

• Bachelor s degree in Computer Science, Information Technology, Engineering, or a related field

Responsibilities

Ensure data quality, reliability, and correctness across large scale Databricks batch pipelines through automated validation and testing practices.

• Own end to end data quality validation for Databricks pipelines across Bronze, Silver, and Gold layers
• Validate data completeness, accuracy, consistency, timeliness, and business rule correctness using Databricks SQL and Delta tables
• Perform dataset, record, schema, and transformation level validations including source to target mapping and derived field checks
• Design, develop, and maintain reusable and scalable data validation frameworks using PySpark and Python on Databricks
• Automate integration, regression, and end to end testing for notebooks, workflows, and scheduled jobs
• Define and implement test data management strategies including data refresh, masking, and environment isolation
• Manage test cases, execution, and defect tracking using Xray and Jira while maintaining test documentation and validation evidence
• Collaborate with engineering, platform, and product teams to enforce data quality standards and communicate risks and release readiness

About the Team

Our Data Platform and Engineering team is responsible for building and maintaining scalable, high quality data solutions that power critical business insights and analytics. By joining this team, you will collaborate with cross-functional experts across engineering, product, and platform functions to drive innovation in modern data architectures using Databricks and Delta Lake. The team is committed to adopting automation, advanced analytics, and responsible AI practices to ensure reliable and high performing data ecosystems.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.