Lead a dedicated team of Data Quality Engineers focused on maintaining the accuracy and reliability of extensive data platforms and pipelines. This pivotal role champions quality strategies, automation advancements, and engineering best practices. Collaborate closely with Data Engineering, Product, and Analytics teams to deliver dependable, business-critical data solutions that drive informed decision-making.

Guide and develop a team of Data Quality Engineers across diverse projects. Formulate and implement robust data quality, automation, and testing strategies for enterprise data platforms. Oversee the validation of ETL processes, business logic, data transformations, and analytics pipelines. Collaborate with Data Engineers, Product Managers, and Analysts to guarantee data accuracy. Manage the creation and upkeep of scalable test automation frameworks. Establish high quality standards and governance for data engineering teams. Integrate CI/CD practices for automated quality checks within data pipelines. Support team growth through hiring, performance management, and career development.

Possess over 8 years of experience in Data Quality Engineering, Software Testing, or Data Engineering. Demonstrate at least 2 years in technical leadership or people management. Exhibit strong proficiency in SQL and Python for data validation. Have hands-on experience with modern data platforms such as Snowflake, Databricks, Airflow, and Spark. Proven track record in building and scaling data quality automation frameworks. Solid understanding of ETL validation, data transformations, and business rule testing. Experience with CI/CD implementation and quality control best practices. Skilled in mentoring, coaching, and developing engineering talent. Excellent communication, stakeholder management, and cross-functional collaboration abilities. Bachelor's degree in Computer Science, Engineering, or equivalent practical experience is required.