Job description
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.