Manager of Data Quality - Data Engineering, Peacock

Our Direct-to-Consumer (DTC) portfolio is a powerhouse collection of consumer-first brands, supported by media industry leaders, Comcast, NBCUniversal and Sky. When you join our team, you’ll work across our dynamic portfolio including Peacock, NOW, Fandango, SkyShowtime, Showmax, and TV Everywhere, powering streaming across more than 70 countries globally. And the evolution doesn’t stop there. With unequalled scale, our teams make the most out of every opportunity to collaborate and learn from one another. We’re always looking for ways to innovate faster, accelerate our growth and consistently offer the very best in consumer experience. But most of all, we’re backed by a culture of respect. We embrace authenticity and inspire people to thrive. As part of the Direct-to-Consumer Decision Sciences team, the Manager of Data Quality will be responsible for overseeing a critical function that bridges data management with operational excellence. The role requires strong cross-functional collaboration skills to effectively engage with software engineering, data analytics, and elements of machine learning to understand data quality requirements and deliver effective solutions. In this role, the Manager of Data Quality will share responsibilities in the development and operation of Data Quality monitors, automation to optimization of data quality pipelines that facilitate deeper analysis and reporting by the business, as well as support ongoing operations related to the Direct to Consumer data ecosystem. The candidate will act as a liaison between data engineering and other teams, advocating for data-driven decision making and best operational practices. Responsibilities include, but are not limited to: Help manage a high-performance team of Data Quality Engineers and Data Quality Analysts Contribute to and lead the team in design, build, testing, scaling and maintaining Data Quality monitors built in-house as well as 3rd party products, according to business and technical requirements. Evaluate and select appropriate technologies and tools for data quality monitoring, ensuring alignment with organizational goals and industry best practices Help Data Engineering organization deliver observable, reliable and secure data quality monitors, embracing “you build it you run it” mentality, and focus on automation and GitOps. Continually work on improving the codebase and have active participation and oversight in all aspects of the team, including agile ceremonies. Take an active role in story definition, assisting business stakeholders with acceptance criteria. Work with Data Engineering Directors to share and contribute to the broader technical vision. Develop and champion best practices, striving towards excellence and raising the bar within the department. Research methods of data anomaly detection using broad range of techniques, including statistical and Machine Learning