Lead Engineer of Data Quality & Applied Research - 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 Lead Engineer of Data Quality & Applied Research 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 and generative AI to deliver robust and effective data quality solutions. In this role, the Lead Engineer of Data Quality & Applied Research will share responsibilities in the development and operation of Data Quality monitors, automation of data quality pipelines reporting of data quality to the business, as well as support ongoing operations related to the Direct to Consumer data ecosystem. They will also be responsible for leading and mentoring the Applied Research engineering team in charge of building innovative solutions utilizing modern paradigms such as Generative AI. 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 & Analysts and Applied Research Engineers. 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 Contribute to and lead experimental projects in Applied Research area, utilizing modern technologies such as Generative AI 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