Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

Lead Data Engineer, Machine Learning

NBCUniversal
Brentford
4 days ago
Create job alert

Job Description

Our Media Group 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 unequaled 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 Media Group Decision Sciences team, the Lead 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 Lead Data Engineer will share responsibilities in the development and maintenance of optimised and highly available data pipelines that facilitate deeper analysis and reporting by the business, as well as support ongoing operations related to the Media Group data ecosystem.


Responsibilities include, but are not limited to:

Help manage a high-performance team of Data Engineers. Contribute to and help lead team in design, build, testing, scaling and maintaining data pipelines from a variety of source systems and streams (internal, third party, cloud based, etc.), according to business and technical requirements. Deliver observable, reliable and secure software, 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 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. Operationalise data processing systems (dev ops).

Qualifications

Qualifications

Extensive relevant experience in Data Engineering. 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: Python, Java, Scala, R, 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. Experience implementing scalable, distributed, and highly available systems using Google Cloud. 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. Data modelling experience (operationalising data science models/products) a plus. Bachelors’ degree with a specialisation in Computer Science, Engineering, Physics, other quantitative field or equivalent industry experience.

Desired Characteristics

Experience with graph-based data workflows using Apache Airflow. Experience building and deploying ML pipelines: training models, feature development, regression testing. 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 recognise 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 NBCUniversal.

Additional Information

As part of our selection process, external candidates may be required to attend an in-person interview with an NBCUniversal employee at one of our locations prior to a hiring decision. NBCUniversal's policy is to provide equal employment opportunities to all applicants and employees without regard to race, color, religion, creed, gender, gender identity or expression, age, national origin or ancestry, citizenship, disability, sexual orientation, marital status, pregnancy, veteran status, membership in the uniformed services, genetic information, or any other basis protected by applicable law.

If you are a qualified individual with a disability or a disabled veteran and require support throughout the application and/or recruitment process as a result of your disability, you have the right to request a reasonable accommodation. You can submit your request to AccessibilityS.

Related Jobs

View all jobs

Lead Data Scientist, Machine Learning Engineer 2025- UK

Senior / Lead Applied Data Scientist - Causal AI for Demand Forecasting.

Lead Machine Learning Engineer - Databricks experience

Lead Machine Learning Engineer - Databricks experience

Lead Machine Learning Engineer - Databricks experience

Lead Machine Learning Engineer - Databricks experience

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Breaking Into Generative AI: A Beginner's Complete Guide to Starting Your Career in 2025/26

Are you fascinated by AI tools like ChatGPT, DALL-E, or Midjourney but unsure how to turn that interest into a career? You're not alone. The generative AI revolution has created thousands of new job opportunities across the UK, and many don't require a computer science degree or years of coding experience. Whether you're a recent graduate, considering a career change, or simply curious about this exciting field, this comprehensive guide will show you exactly how to break into generative AI jobs.

Pre-Employment Checks for AI Jobs: DBS, References & Right-to-Work and more Explained

The artificial intelligence sector in the UK is experiencing unprecedented growth, with companies across industries seeking talented professionals to drive digital transformation. However, securing a position in this competitive field involves more than just demonstrating technical expertise. Pre-employment checks have become an integral part of the hiring process for AI jobs, ensuring organisations maintain security, compliance, and trust whilst building their teams. Whether you're a data scientist, machine learning engineer, AI researcher, or technology consultant, understanding the pre-employment screening process is crucial for navigating your career journey successfully. This comprehensive guide explores the various types of background checks you may encounter when applying for AI positions in the UK, from basic right-to-work verification to enhanced security clearance requirements.

Why Now Is the Perfect Time to Retrain and Launch Your Career in Artificial Intelligence

The artificial intelligence revolution isn't coming—it's here. From the bustling tech hubs of London and Manchester to the emerging AI clusters in Edinburgh and Cambridge, the UK is experiencing an unprecedented demand for skilled AI professionals. If you've been considering a career change or looking to future-proof your professional trajectory, there has never been a better time to retrain and enter the field of artificial intelligence.