Senior Data Engineer

BBC
London
2 months ago
Applications closed

Related Jobs

View all jobs

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

Senior Data Engineer

This job is with BBC, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

JOB DETAILS

JOB BAND: D
CONTRACT TYPE: Permanent, Full-time
DEPARTMENT: BBC Product Group
LOCATION: London, Salford, Newcastle, Cardiff, Glasgow - Hybrid
PROPOSED SALARY RANGE: Up to £69,773 depending on relevant skills, knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights.
We're happy to discuss flexible working. If you'd like to, please indicate your preference in the application - though there's no obligation to do so now. Flexible working will be part of the discussion at offer stage.
PURPOSE OF THE ROLE

The Senior Data Engineer is a role that will support the Product Data Domain teams.

You will help to build ETL pipelines to ingest and transform data to develop the data products that will power key value use cases across the BBC. You will work in an agile multi-disciplinary team alongside product analytics developers, product data managers, data modelers and data operations managers, ensuring that all work delivers maximum value to the BBC.
WHY JOIN THE TEAM
You will be working on cross-product strategic projects and cutting-edge technologies, surrounded by like-minded people.

This work will align with and help inform the short and long-term data strategy.

This is an individual contributor role that, while it does involve the mentoring of colleagues, will not involve line management responsibilities.
YOUR KEY RESPONSIBILITIES AND IMPACT:
Role and responsibilities will comprise of:
·

Develop robust and scalable data pipelines to ingest, transform, and analyse large volumes of structured and unstructured data from diverse data sources. Pipelines must be optimised for performance, reliability, and scalability in line with the BBC's scale.
·

Contributes to initiatives to enhance data quality, governance and security across the organisation, ensuring compliance with BBC guidelines and industry best practices.
·

Breaking down stakeholders requirements into smaller tasks and identify the best solution.
·

Builds innovative solutions to acquiring and enriching data from a variety of data sources.
·

Works on one or more projects guiding other team members on designing and developing, testing, and building automation workflows.
·

Conducts insightful and physical database design, designs key and indexing schemes and designs partitioning.
·

Participates in building and testing business continuity & disaster recovery procedures per requirements.
·

Evaluates and provides feedback on future technologies and new releases/upgrades based on their market knowledge of the domain when asked to do so.
YOUR SKILLS AND EXPERIENCE

Essential Skills
•

Extensive (3+ years) experience in a data engineering or analytics engineering role, preferably in digital products, building ETL pipelines, ingesting data from a diverse set of data sources (including event streams, various forms of batch processing)
•

Excellent SQL and python skills with experience in deploying and scheduling code bases in a data development environment, using technologies such as Airflow.
•

Good working knowledge of cloud-based Data Warehousing technologies (such as AWS Redshift, GCP BigQuery or Snowflake)
•

Demonstrable experience of working alongside cross-functional teams interacting with Product Managers, Infrastructure Engineers, Data Scientists, and Data Analysts
•

Strong stakeholder management skills with the ability to prioritise and a structured approach and ability to bring others on the journey
Desirable Skills
•

Ability to listen to others' ideas and build on them
•

Ability to clearly communicate to both technical and non-technical audiences
•

Ability to collaborate effectively, working alongside other team members towards the team's goals, and enabling others to succeed, where possible
•

Strong attention to detail
If you can bring some of these skills and experience, along with transferable strengths, we'd love to hear from you and encourage you to apply.
Before your start date, you may need to disclose any unspent convictions or police charges, in line with our Contracts of Employment policy. This allows us to discuss any support you may need and assess any risks. Failure to disclose may result in the withdrawal of your offer.

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

Careers Jobs

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.