This role leads a team focused on ensuring the accuracy and reliability of large-scale data platforms. You will shape quality strategies, drive automation, and foster engineering excellence. Collaboration with Data Engineering, Product, and Analytics teams is key to delivering trusted, business-critical data solutions.

Success in this position involves building high-performing teams through mentorship and strong leadership. You will drive data quality excellence with scalable automation and robust testing strategies, ultimately improving data reliability across critical platforms. Establishing engineering standards for efficiency and consistency is also paramount, ensuring trusted data for informed business and product decisions.

Lead and mentor a team of Data Quality Engineers, defining and executing comprehensive data quality, automation, and testing strategies for enterprise data platforms.

Drive validation of ETL pipelines, business rules, and data transformations, partnering closely with Data Engineers, Product Managers, and Analysts. Oversee the development and maintenance of scalable test automation frameworks.

Establish quality standards and best practices across data engineering teams, integrating CI/CD for automated quality checks. Support team development through hiring, performance management, and career growth initiatives, while leading technical improvements and promoting continuous learning.

Requires a minimum of 8 years in Data Quality Engineering, Software Testing, or Data Engineering, with at least 2 years in technical leadership or people management.

Proficiency in SQL and Python is essential for validating large datasets and workflows, alongside experience with modern data platforms like Snowflake, Databricks, Airflow, and Spark. Proven ability to build and scale data quality automation frameworks and a strong grasp of ETL validation, data transformations, and business rule testing are crucial.

Experience implementing CI/CD pipelines and quality controls is expected. The role demands strong mentoring, coaching, and talent development skills, coupled with excellent communication, stakeholder management, and cross-functional collaboration abilities. A Bachelor's degree in Computer Science, Engineering, or equivalent practical experience is required.