At a Glance
- Tasks: Design and implement scalable data pipelines for our multimodal AI platform.
- Company: Join Fox Corporation, a leader in media and entertainment.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Collaborative environment with mentorship opportunities and cutting-edge projects.
- Why this job: Be at the forefront of AI technology and make a significant impact.
- Qualifications: Extensive data engineering experience and proficiency in Python and SQL.
The predicted salary is between 80000 - 100000 £ per year.
Fox Corporation produces and distributes content through leading brands, including FOX News Media, FOX Sports, FOX Entertainment, FOX Television Stations, and Tubi Media Group. We empower a diverse range of creators to develop culturally significant content while building an organization that thrives on creative ideas, operational expertise, and strategic thinking.
We are seeking a Staff Data Engineer to join our Emerging Tech team and define the data architecture powering our multimodal AI platform. You will set the technical vision and drive the implementation of scalable data pipelines, lakehouse infrastructure, and data platform capabilities that enable content intelligence, semantic search, recommendation, and personalization at scale.
Responsibilities:
- Act as the technical anchor for your product pillar — collaborate closely with product leaders, ML engineers, backend engineers, editorial, and merchandising teams to translate ambiguous goals into clear technical designs, and communicate decisions effectively to both technical and non-technical stakeholders.
- Design and hands-on implement high-throughput batch and streaming data pipelines for multimodal content — including media segments, metadata, transcripts, and engagement signals — and architect the data models and ML feature stores that support them.
- Build scalable data ingestion frameworks across heterogeneous sources including media processing systems, AI inference services, and user engagement events; partner with ML engineers to define feature-ready data contracts for model training and inference, including embedding generation and vector storage.
- Own data governance, lineage tracking, and quality frameworks; design observability and alerting to ensure data integrity and SLA compliance at scale.
- Drive pipeline performance optimization and cloud cost management; lead adoption of CI/CD and infrastructure-as-code practices across the team.
- Mentor data engineers at all levels, conduct design and code reviews, and evaluate emerging technologies to ensure the team's technical decisions align with platform strategy, security, and compliance requirements.
What You Will Need:
- Extensive data engineering experience operating production systems at scale in global engineering organizations.
- Expert-level proficiency in Python and SQL for large-scale data processing and transformation.
- Deep experience with distributed data processing frameworks (Apache Spark, Apache Flink, or equivalent) and streaming architectures (Kafka, Spark Structured Streaming) for both batch and real-time workloads at terabyte scale.
- Proven experience building data infrastructure for LLM and generative AI workloads — including training data preparation, embedding generation, and vector storage.
- Proven ability to provide technical clarity in ambiguous environments — translating loosely defined product goals into actionable architecture decisions and driving alignment across engineering, ML, and product stakeholders.
- Strong cloud platform experience on GCP, AWS, or Azure with hands-on infrastructure-as-code (Terraform or CDK) and DevOps practices.
- Deep understanding of data warehousing, data mesh principles, and open table format standards (Apache Iceberg, Delta Lake, or Apache Hudi).
- Ownership mindset with end-to-end accountability for architecture, implementation, and production operations.
NICE TO HAVE, BUT NOT A DEALBREAKER:
- Experience with managed lakehouse platforms (Databricks or equivalent) and their ecosystem tooling.
- Knowledge of media data formats, content metadata standards, or media processing pipelines.
- Experience with observability and monitoring systems (Datadog, Grafana, or OpenTelemetry).
- Experience leading data platform migrations or large-scale data infrastructure initiatives.
- Contributions to open-source data engineering projects or active participation in the data engineering community.
- Curiosity and enthusiasm for multimodal AI, generative AI, and LLM-powered applications.
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.
Staff Data Engineer in London employer: FOX Tech
Contact Detail:
FOX Tech Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Fox or similar companies. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repo showcasing your data engineering projects. This is your chance to demonstrate your expertise in Python, SQL, and any cool frameworks you've worked with.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both techies and non-techies.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining the team at Fox.
We think you need these skills to ace Staff Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Staff Data Engineer role. Highlight your experience with data pipelines, cloud platforms, and any relevant projects that showcase your skills in Python and SQL. We want to see how your background aligns with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering and how you can contribute to our Emerging Tech team. Be sure to mention specific experiences that relate to the job description.
Showcase Your Technical Skills: In your application, don't shy away from showcasing your technical skills. Mention your proficiency in distributed data processing frameworks and any hands-on experience with cloud platforms. We love seeing candidates who can demonstrate their expertise!
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s super easy, and you'll be able to keep track of your application status. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at FOX Tech
✨Know Your Data Inside Out
Make sure you’re well-versed in the data engineering concepts relevant to the role. Brush up on your knowledge of Python, SQL, and distributed data processing frameworks like Apache Spark or Kafka. Being able to discuss your experience with these technologies confidently will show that you’re ready to tackle the challenges of the position.
✨Prepare for Technical Questions
Expect to face technical questions that assess your problem-solving skills and understanding of data architecture. Practice explaining how you would design scalable data pipelines or handle data governance issues. Use real-world examples from your past experiences to illustrate your thought process and decision-making.
✨Showcase Your Collaboration Skills
As a Staff Data Engineer, you’ll need to work closely with various teams. Be prepared to discuss how you’ve collaborated with product leaders, ML engineers, and other stakeholders in previous roles. Highlight specific instances where you translated complex technical concepts into clear communication for non-technical team members.
✨Demonstrate Your Ownership Mindset
The role requires an ownership mindset, so be ready to talk about projects where you took full responsibility from architecture to implementation. Share examples of how you ensured data integrity and compliance, and how you’ve mentored others in your team. This will show that you’re not just a doer but also a leader who can elevate the entire team.