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Sr. Data Engineer

Company
NBCUniversal
Location
New York, NY
Work type
Full Time · Hybrid
Posted
2026-09-22

Job description

Job Description
The Media Group at NBCU supports a powerhouse collection of consumer-first brands including Peacock, NBC, Bravo, NBC Sports, and NBCU International. 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 our Senior Data Engineer, you’ll join the Content Delivery Engineering team (CDE) within NBCUniversal’s Global Video Engineering organization in New York City, USA. The Senior 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, Senior 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

Design, develop & maintain new and existing data systems and pipelines, with a focus on reliability, testability and ease of use.
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
Ensure a consistent, diligent approach to peer review of code and configuration change within sensible, maintained repository structures and CI/CD pipelined deployment.
Participate in, or lead design reviews, architectural discussions and team knowledge‑sharing sessions with peers and stakeholders.
Make best use of our observability systems & advanced analytics to surface issues, drive diagnosis and develop fixes.
Qualifications
Bachelor's degree in computer science, information technology, or a relevant field is required.
5+ years of experience in working with big data: ETL, pipeline building, analysis and code, with expertise in at least one programming language
Experience implementing scalable, distributed, highly available, and resilient systems using industry standard data platforms (Snowflake, Databricks, GCP, AWS, etc.)
Skilled with using software repositories, CI/CD pipelines and test automation.
Experience with data visualization tools and techniques
Strong skills in data processing using SQL
Experience with Site Reliability Engineering (SRE) practices for ensuring scalability and reliability in cloud environments.
Familiarity with Agile methodologies (Scrum and Kanban).
A flair for communicating clearly via design document, text, voice and code to a wide variety of nationalities.
Knowledge and/or production exposure to using CDNs to deliver streaming media is advantageous or full training can be provided.

Desired Characteristics

Experience with Snowflake or similar data service
Experience with data visualizations
Experience with multi-billion record datasets and leading projects that span the disciplines of data science and data engineering
Knowledge of enterprise-level digital analytics platforms
Team oriented and collaborative approach with a demonstrated aptitude and willingness to learn new methods and tools
Pride and ownership in your work and confident representation of your team to other parts of NBCUniversal

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