Join our team as a Manager, Data Quality Engineering, leading a dedicated group of professionals. You will be instrumental in upholding the accuracy, reliability, and integrity of extensive data platforms and pipelines. This pivotal role spearheads quality initiatives, drives automation advancements, and fosters engineering excellence. Collaboration with Data Engineering, Product, and Analytics teams is key to delivering dependable, business-critical data solutions.

Success in this position involves building high-performing teams through effective coaching and leadership, driving exceptional data quality via scalable automation, and enhancing data reliability across essential business platforms. You will also be responsible for establishing robust engineering standards to boost efficiency, consistency, and overall quality, ultimately delivering significant organizational impact by ensuring trustworthy data for strategic business and product decisions.

As a leader, you will guide and inspire a team of Data Quality Engineers across various projects and areas. Your focus will be on defining and implementing comprehensive data quality, automation, and testing strategies for enterprise-scale data platforms. This includes driving the validation of ETL pipelines, business rules, data transformations, and analytics workflows. You will collaborate closely with Data Engineers, Product Managers, and Analysts to guarantee data accuracy and trustworthiness, while overseeing the development and maintenance of scalable test automation frameworks.

Establishing quality standards, best practices, and governance across data engineering teams is crucial. You will drive CI/CD integration and automated quality checks within data pipelines. Additionally, you will support team growth through hiring, performance management, and career development. Leading technical initiatives and promoting continuous improvement in quality engineering processes will be part of your mandate, alongside influencing long-term quality strategy, tooling decisions, and organizational effectiveness.

We are seeking experienced professionals with a minimum of 8 years in Data Quality Engineering, Software Testing, or Data Engineering. A proven track record of at least 2 years in technical leadership or people management roles is essential. Candidates must possess strong expertise in SQL and Python for validating large datasets and data workflows, alongside experience with modern data platforms like Snowflake, Databricks, Airflow, and Spark.

Demonstrated success in building and scaling data quality automation frameworks is required. A solid understanding of ETL validation, data transformations, and business rule testing is necessary. Experience with implementing CI/CD pipelines, quality controls, and testing best practices is also expected. Strong abilities in mentoring, coaching, and developing engineering talent, coupled with excellent communication, stakeholder management, and cross-functional collaboration skills, are vital for this role. A Bachelor's degree in Computer Science, Engineering, or equivalent practical experience is required.