Assistant Manager | QA | Bengaluru | Engineering as a Service/ Operate

About the Role

The Manager, Data Quality Engineering (M2) leads a team of Data Quality Engineers responsible for ensuring the accuracy, reliability, and integrity of large-scale data platforms and pipelines. This role drives quality strategy, automation initiatives, and engineering excellence while partnering with Data Engineering, Product, and Analytics teams to deliver trusted, business-critical data solutions.

Responsibilities

• Lead and mentor a team of Data Quality Engineers across multiple projects and domains.
• Define and execute data quality, automation, and testing strategies for enterprise-scale data platforms.
• Drive validation of ETL pipelines, business rules, data transformations, and analytics workflows.
• Partner with Data Engineers, Product Managers, and Analysts to ensure data accuracy and trustworthiness.
• Oversee the design, development, and maintenance of scalable test automation frameworks.
• Establish quality standards, best practices, and governance across data engineering teams.
• Drive CI/CD integration and automated quality checks within data pipelines.
• Support hiring, performance management, career growth, and team development.
• Lead technical initiatives and promote continuous improvement across quality engineering processes.
• Influence long-term quality strategy, tooling decisions, and organizational effectiveness.

Requirements

• 8+ years of experience in Data Quality Engineering, Software Testing, or Data Engineering.
• 2+ years of experience in technical leadership or people management roles.
• Strong expertise in SQL and Python for validating large-scale datasets and data workflows.
• Experience with Snowflake, Databricks, Airflow, Spark, and modern data platforms.
• Proven experience building and scaling data quality automation frameworks.
• Strong understanding of ETL validation, data transformations, and business rule testing.
• Experience implementing CI/CD pipelines, quality controls, and testing best practices.
• Demonstrated ability to mentor, coach, and develop engineering talent.
• Strong communication, stakeholder management, and cross-functional collaboration skills.
• Bachelor's degree in Computer Science, Engineering, or equivalent practical experience.

Success at M2

• Builds High-Performing Teams through coaching, mentorship, and strong leadership.
• Drives Data Quality Excellence with scalable automation and testing strategies.
• Improves Data Reliability across critical business platforms and pipelines.
• Establishes Engineering Standards that increase efficiency, consistency, and quality.
• Delivers Organizational Impact by ensuring trusted data for business and product decisions.