Director Of Data Science
New York, NY US
Meet Peacock, NBCUniversal's new, wildly entertaining streaming service that combines timeless shows and movies with timely news, sports and pop-culture.
We're growing our team of smart, hungry, and upbeat doers who crave the chance to build something new at the epicenter of content, tech, and culture. We need fearless leaders and pop-culture fiends who work hard and fan hard. Creative problem-solvers who just so happen to be the reigning champs at Parks & Rec trivia night. So if this sounds like you, join our flock. And we promise, we won't put your stapler in Jell-O.
As part of the Direct-to-Consumer Decision Sciences team, the Data Engineer will be responsible for creating a connected data ecosystem that unleashes the power of our streaming data. We gather data from across all customer/prospect journeys in near real-time, to allow fast feedback loops across territories; combined with our strategic data platform, this data ecosystem is at the core of being able to make intelligent customer and business decisions.
In this role, the Data Engineer will share responsibilities in the development and maintenance of an optimized and highly available data pipelines that facilitate deeper analysis and reporting by the business, as well as support ongoing operations related to the Direct to Consumer data ecosystem
Responsibilities include, but are not limited to:
• Design, build, test, scale and maintain data pipelines from a variety of source systems and streams (Internal, third party, cloud based, etc.), according to business and technical requirements.
• Continually work on improving the codebase and have active participation in all aspects of the team, including agile ceremonies.
• Take an active role in story definition, assisting business stakeholders with acceptance criteria.
• Work with Principal Engineers and Architects to share and contribute to the broader technical vision.
• Develop and champion best practices, striving towards excellence and raising the bar within the department.
• Develop solutions combining data blending, profiling, mining, statistical analysis, and machine learning, to better define and curate models, test hypothesis, and deliver key insights
• Operationalize data processing systems (dev ops)
• Experience of near Real Time & Batch Data Pipeline development in a similar Big Data Engineering role.
• Programming skills in one or more of the following: Java, Scala, R, Python, SQL and experience in writing reusable/efficient code to automate analysis and data processes
• Experience in processing structured and unstructured data into a form suitable for analysis and reporting with integration with a variety of data metric providers ranging from advertising, web analytics, and consumer devices
• Hands on programming experience of the following (or similar) technologies: Apache Beam, Scio, Apache Spark, and Snowflake.
• Experience in progressive data application development, working in large scale/distributed SQL, NoSQL, and/or Hadoop environment.
• Build and maintain dimensional data warehouses in support of BI tools
• Develop data catalogs and data cleanliness to ensure clarity and correctness of key business metrics
• Experience building streaming data pipelines using Kafka, Spark, or Flink
• Bachelors' degree with a specialization in Computer Science, Engineering, Physics, other quantitative field or equivalent industry experience.
• Experience with graph-based data workflows using Apache Airflow
• Experience building and deploying ML pipelines: training models, feature development, regression testing
• Data modelling experience (operationalizing data science models/products)
• Experience with cloud environments such as AWS, GCP, or Azure
• Strong Test-Driven Development background, with understanding of levels of testing required to continuously deliver value to production.
• Experience with large-scale video assets
• Ability to work effectively across functions, disciplines, and levels
• Team-oriented and collaborative approach with a demonstrated aptitude, enthusiasm and willingness to learn new methods, tools, practices and skills
• Ability to recognize discordant views and take part in constructive dialogue to resolve them
• Pride and ownership in your work and confident representation of your team to other parts of
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