Director, Data & Analytics

Company Description

We create world-class content, which we distribute across our portfolio of film, television, and streaming, and bring to life through our theme parks and consumer experiences. We own and operate leading entertainment and news brands, including NBC, NBC News, MSNBC, CNBC, NBC Sports, Telemundo, NBC Local Stations, Bravo, USA Network, and Peacock, our premium ad-supported streaming service. We produce and distribute premier filmed entertainment and programming through Universal Filmed Entertainment Group and Universal Studio Group, and have world-renowned theme parks and attractions through Universal Destinations & Experiences. NBCUniversal is a subsidiary of Comcast Corporation.

Here you can be your authentic self. As a company uniquely positioned to educate, entertain and empower through our platforms, Comcast NBCUniversal stands for including everyone. Our Diversity, Equity and Inclusion initiatives, coupled with our Corporate Social Responsibility work, is informed by our employees, audiences, park guests and the communities in which we live. We strive to foster a diverse, equitable and inclusive culture where our employees feel supported, embraced and heard. Together, we’ll continue to create and deliver content that reflects the current and ever-changing face of the world.

Job Description

As part of the global Operations & Technology organization, the Enterprise Data & Analytics Engineering team is focused on creating data platforms, pipelines, and analytical solutions across our television, direct-to-consumer, studios, and parks businesses. We pride ourselves on providing our decision-makers and leaders with data-driven insights to help shape and guide NBCUniversal's content, products, and experiences.

NBCUniversal is on the hunt for a game-changing Data & Analytics Director who's ready to take on the challenge of creating the next-gen enterprise data solutions across the organization.

In this role, you'll be leading a team of brilliant engineers, working alongside product leaders and other engineering teams to achieve our mission of scaling enterprise data assets that are reusable, extensible, and generate the most value for our company. If you're a technical mastermind with a passion for building modern data solutions at scale, then we've got a role that's tailor-made for you. Join us! 

Responsibilities:

• Plan and execute data and analytics engineering programs, formulate strategies for solving business problems, and develop capabilities to scale the impact of data through the development of self-service analytics and insights
• Architect and build data solutions across multiple domains, specifically within Content Production Analytics
• Partner with data scientists, business solutions, enterprise product, and engineering teams, to deliver data and analytics that advance our mission to be a data-driven company transforming the industry
• Implement scalable data processes to achieve 99.99% reliability and availability
• Grow the technical expertise of the team - build and lead a team of data engineers, ML engineers, data visualization and analytics engineers through hiring, coaching, mentoring, feedback, and hands-on career development
• Organize and socialize metadata resources, such as data lineage documents, data mappings, data dictionaries, training documents, knowledge base/wiki, etc. 
• Investigate new and developing technologies as they appear in industry and academia and determine how to leverage these new technologies into our data solutions

Qualifications

• 10+ years of experience architecting and building data solutions at scale
• 5+ years relevant experience in delivering data platforms, data governance at an enterprise level and leading a data management and platform engineering team 
• Hands-on production workload experience with cloud data platforms at scale (Snowflake, AWS Redshift, GCP Big Query and/or Azure Synapse)
• Experience building data pipelines, ideally using SQL, Python, Spark, dbt, and orchestrated in Apache Airflow, MWAA (Amazon Managed Workflows for Apache Airflow); Google Cloud Dataflow is a huge plus
• Working experience unlocking the value of data with visualization tools (Tableau, Power BI, Looker, Data Studio)
• Passion for data science and machine learning using R, Databricks and ability to operationalize models
• Expertise in data modeling and establishing data architecture across multiple systems
• Proficiency in Python, or willingness to grow into Python from your other scripting languages (i.e., Java, Scala)
• Knowledge of data federation technologies (Starburst, Dremio, Presto) and working understanding of data models and how they