Skills and Competencies : - 6+ years of experience in Software Quality Assurance or Data Quality Engineering, including automation - first testing for complex enterprise data platforms- Strong hands - on experience with Databricks SQL and Python, including testing of notebooks, workflows, pipelines, and scheduled jobs- Solid understanding of Medallion architecture (Bronze, Silver, Gold) and data lifecycle validation practices across enterprise data ecosystems- Expertise in PySpark for data validation, test automation, and building scalable, reusable testing frameworks- Robust proficiency in SQL and data validation techniques across dataset, record, schema, transformation, and source - to - target mapping levels- Experience working in Agile or Scrum environments with tools such as Xray for test management and Jira for defect tracking- Proven experience leading quality assurance initiatives, mentoring team members, driving quality governance, managing stakeholder expectations, and influencing delivery decisions- 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 fieldResponsibilities : - Ensure data quality, reliability, and correctness across large - scale data platform pipelines through automated validation and testing practices- Lead end - to - end data quality validation across Bronze, Silver, and Gold data layers, establishing testing standards and quality gates across projects- Define and drive the overall quality assurance strategy, test approach, automation roadmap, and release readiness criteria for enterprise data platform initiatives- Mentor and provide technical leadership to quality assurance engineers by reviewing test plans, automation frameworks, validation logic, defect analysis, and quality metrics- Collaborate with engineering, platform, product, and architecture teams to influence solution design, identify quality risks early, and ensure testability of data solutions- Own quality governance activities including test execution reviews, defect triage, risk assessments, root cause analysis, and executive - level status reporting- Drive continuous improvement initiatives by identifying opportunities to enhance automation coverage, testing efficiency, data quality controls, and operational excellence- Act as the primary quality assurance point of contact for stakeholders, providing leadership during releases, production validation, issue resolution, and audit or compliance reviews (ref:hirist.tech)

📌 Moody's - Assistant Director - Quality Assurance (Bengaluru)
🏢 Moody's Shared Services India Private
📍 Bengaluru