Senior Data Engineer
BBC is hiring a Senior Data Engineer in London, United Kingdom. It pays £55k-£65k a year and Level rates it ; you can apply on BBC.
Level's read on this job
- Level rates this data engineer role Uses AI ●●○○: an ordinary role that requires AI tools.
- Tools and skills the posting cites include Bedrock and RAG.
- Level classifies it as a senior role.
- Level lists 34 other open roles at BBC.
- The role was posted in the last few days.
AI in this role
JOB DETAILS
JOB BAND: D
CONTRACT TYPE: x1 Permanent and x1 12 month FTC / Attachment, Full-time
DEPARTMENT: CCOG Data Engineering
LOCATION: Salford or London / Hybrid
PROPOSED SALARY RANGE: £55,000 - £65,000 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 plays a key role within the Audience Data team, designing, building and maintaining the data pipelines and infrastructure that enable teams across the BBC to make effective use of data. Working closely with Analytics, Data Science, Marketing, Brand and other business functions, the role is responsible for delivering reliable, scalable and trusted data solutions that support audience insight, engagement and decision-making.
WHY JOIN THE TEAM
The BBC aims to stimulate and delight audiences across the UK with distinctive, creative content. To support this aim, BBC is entering a new charter period of significant and exciting change, developing new capabilities in order to define a BBC fit for the next generation.
YOUR KEY RESPONSIBILITIES AND IMPACT
- Design, build and maintain scalable cloud-based data pipelines and data products supporting audience growth, CRM activation, marketing measurement and performance analytics.
- Build and maintain integrations between BBC Account, mParticle, CRM platforms, marketing technologies, advertising platforms and enterprise reporting systems.
- Develop robust API-based integrations to enable secure and reliable exchange of data across marketing, product, audience and analytics platforms.
- Collaborate with analysts, data scientists, engineers, product managers and business stakeholders to identify opportunities for automation, optimisation and improved decision making.
- Ensure all solutions are designed and implemented in accordance with BBC standards for privacy, data governance, security, consent management and international regulatory compliance.
YOUR SKILLS AND EXPERIENCE
ESSENTIAL CRITERIA
- Strong experience designing, building and maintaining scalable data pipelines and integration solutions using Apache Airflow (or similar orchestration platforms), Python, SQL and bash/linux.
- Experience developing cloud-native data platforms and solutions on AWS, including working with cloud data warehouse technologies such as Amazon Redshift and applying data modelling best practices.
- Good understanding of software engineering principles, including object-oriented development, testing practices, version control, code quality management, CI/CD deployment processes, containerisation, and LLM-assisted coding.
- Experience working with data processing and database technologies, including relational databases, query optimisation, performance tuning, monitoring, backup and recovery, and an understanding of different data structures and their appropriate use cases.
- Experience delivering data integrations for Customer Data Platforms (CDPs) and external data sources, including technologies such as mParticle, Twilio Segment, or similar customer data and marketing technology platforms.
DESIRABLE
- Experience implementing layered data architecture patterns (e.g. Medallion Architecture, Data Warehouse or Lakehouse approaches) to support data quality, governance and scalability.
- Contributing to the development of area of specialism or industry domain
- Broadcast, production, start-up or media experience
- A mix of public sector and commercial experience
- Successful academic background in your specialist discipline
- Familiarity with Retrieval-Augmented Generation (RAG), vector databases, embeddings, and other patterns used to support Generative AI solutions on platforms such as Amazon Bedrock.
- Experience developing data-based apps in Streamlit/Shiny
- Skills in ‘Big Data’ technology tools like Hadoop/Spark
- Knowledge of Infrastructure as Code tools like CloudFormation/Terraform
If you can bring some of these skills and experiences, 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.
How we rate this
Senior Data Engineer at BBC rates 42 out of 100 for how much of the daily work is AI. That makes it Uses AI (AI Level 2 of 4). The level is about AI in the job, not seniority.
Uses AI. An ordinary role that requires AI tools.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
Use the typical data engineer figure as a reference when pay comes up. See data engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through how you've used Bedrock in your day-to-day work.
- This role expects you to use AI tools as part of the job. Which ones have you used, and for what?
- Tell me about a time an AI tool got something wrong. How did you catch it?
Adapt your resume
- List these exact terms on your resume: RAG and Bedrock. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Put the AI tool in a bullet point about what you did, not just in a skills list. This role treats it as a required part of the job.
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