Lead a team of Data Quality Engineers to ensure the accuracy, reliability, and integrity of large-scale data platforms. This role is pivotal in driving quality strategy, automation initiatives, and engineering excellence. You will collaborate closely with Data Engineering, Product, and Analytics teams to deliver trusted, business-critical data solutions.

Success in this position involves building high-performing teams, driving data quality excellence through scalable automation, and improving data reliability across critical business platforms and pipelines. You will establish engineering standards that enhance efficiency, consistency, and overall quality, ensuring the delivery of trusted data for crucial business and product decisions.

Guide and mentor Data Quality Engineers across various projects. Develop and implement comprehensive data quality, automation, and testing strategies for enterprise data platforms. Validate ETL pipelines, business rules, data transformations, and analytics workflows. Collaborate with Data Engineers, Product Managers, and Analysts to maintain data accuracy. Oversee the creation and maintenance of scalable test automation frameworks. Establish quality standards and best practices for data engineering teams. Integrate CI/CD practices and automated quality checks within data pipelines. Support team growth through hiring, performance management, and development. Lead technical initiatives and foster continuous improvement in quality engineering. Influence long-term quality strategy and tooling decisions.

Requires 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. Experience with modern data platforms like Snowflake, Databricks, Airflow, and Spark is expected. Demonstrated ability to build and scale data quality automation frameworks and strong understanding of ETL validation and business rule testing. Experience implementing CI/CD pipelines and quality controls is necessary. Proven skills in mentoring, coaching, and developing engineering talent, alongside strong communication and stakeholder management abilities. A Bachelor's degree in Computer Science, Engineering, or equivalent practical experience is required.