CDE Data Engineer

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. The CDE Data Engineer will join the Content Delivery Engineering team, within the Global Video Engineering organization at NBCUniversal. The CDE Data Engineer will be responsible for implementing and maintaining systems that ingest, process, and store vast amounts of data from internal systems and external partner systems. These data systems must be scalable, robust, and within budget. In this role, the CDE Data Engineer will work with a variety of technologies that support the building of meaningful models, alerts, reports, and visualizations from vast quantities of data. Responsibilities include, but are not limited to Development of data systems and pipelines Assist in cleansing, discretization, imputation, selection, generalization etc. to create high quality features for the modeling process Work with business stakeholders to define business requirements including KPI and acceptance criteria Use big data, relational and non-relational data sources, to access data at the appropriate level of granularity for the needs of specific analytical projects Maintain up to date knowledge of the relevant data set structures and participate in defining necessary upgrades and modifications Collaborate with software and data architects in building real-time and automated batch implementations of the data science solutions and integrating them into the streaming service architecture Drive work on improving the codebase, striving for ultimate efficiencies in code and performance