Principal Product Analytics Developer /Team Lead, Newcastle

BBC
Edinburgh
2 months ago
Applications closed

Related Jobs

View all jobs

Powertrain Software Engineer

Principal Data Scientist – Operational Research, Simulation & ML (Basé à Hounslow)

Senior Data Engineer (Azure Synapse) - London

Change Manager

Principal Data Science Consultant - Gen AI Specialist

Enterprise Data Architect London, Agile (Basé à London)

Job Band

Job number 20622
Job Band: D
Starting salary: up to £71,500 depending on relevant skills, knowledge and experience. The expected salary range for this role reflects internal benchmarking and external market insights
Contract Type: Continuing
Location: Newcastle, Hybrid with at least one day a fortnight on site 

Excellent career progression – the BBC offers great opportunities for employees to seek new challenges and work in different areas of the organisation.


Unrivalled training and development opportunities – our in-house Academy hosts a wide range of internal and external courses and certification.


Benefits - We offer a negotiable salary package, a flexible 35-hour working week for work-life balance and 25 days annual leave with the option to buy an extra 5 days, a defined pension scheme and discounted dental, health care and gym. You can find out more about working at the BBC by selecting this link to our candidate pack Here.


If you need to discuss adjustments or access requirements for the interview process please contact the k.

For any general queries, please contact: k.

Freelancers are eligible to apply for an internal role if they are on a Worker Contract and they have worked continuously for 6 months. If they have worked for less than 6 months continuously or have a break of 3 weeks or more between engagements, they must seek Divisional HR approval to apply for an internal role prior to submitting an application.

Interview Process

This is a 2-stage interview process. Both are virtual for shortlisted candidates; the first is a 30-min technical interview based on your experience, the second is a 1-hour interview focusing on a take home exercise, competency, and values-based questions. Interviews will begin the week commencing 3rd February 2025.

Introduction

Product Group is responsible for the design, development, and delivery of the BBC’s portfolio of digital products.

Including iPlayer, Sounds, Bitesize, and the BBC News and BBC Sport apps and website, our portfolio is diverse and contains some of the largest and highest-profile properties on the UK internet. We’re a huge streaming media destination, a news source trusted across the world, a provider of educational and entertaining content to children of all ages, and a sports results, analysis, and commentary service, and much more besides. It's an unparalleled portfolio of products, and our strength is our range and breadth. Working with the BBC’s content divisions, our focus now is on driving engagement across our portfolio so that the BBC online becomes a valued daily habit for all audiences just as television and radio have been over the last century.

Data is fundamental to our future: both in helping us prioritise and shape our work and in creating richer, more personalised experiences for our audiences. And our portfolio means that we’ve got one of the widest, most diverse, and most exciting datasets to work within the UK.

Key Responsibilities

The Principal Analytics Team lead is a new role that will support the newly created Product Data Domain teams. Working as part of our multi-disciplinary data teams, you will lead on the creation of clean, tested, well-modelled trusted datasets around our digital estate for use across the BBC, including managing a team focused on collecting data. Sitting between data engineering and data analysis you will get exposure to both areas across all product teams and focus on modelling unstructured data into meaningful insights. You will be building and maintaining data pipelines through best practices to support teams across the BBC in delivering quality products and content.

You will be leading on work to break down business requirements, designing the dimensional data models and build ETL pipelines using SQL to deliver data products that will power key value use cases across the BBC. The role requires strong skills in dimensionally modelling, conforming and integrating data from multiple sources, as well as experience in leading strong analytics engineering teams.

You will work alongside other product analytics developers, product data managers, data engineers and data operations managers, ensuring that all work delivers maximum value to the BBC. You will be leading on cross-product strategic projects and using cutting-edge technologies, surrounded by like-minded people. This work will align with and help inform the short and long-term data strategy. This role may involve line management responsibilities.

Role and responsibilities will comprise of:

· Planning workloads and delegating tasks in agile environment
· Assisting with the daily operation of the organisation, including support and incidents 
· Able to provide feedback to team members, including constructive areas for development
· Leading on the design, implementation and maintenance of dimensional data models that promote a self-service approach to data consumption. This includes ensuring that data quality within the data warehouse is maintained throughout the data lifecycle.
· Define best practices in dimensional data modelling and database design and ensure standards are adhered to across the team.
· Mentoring, coaching and supporting other team members in developing data modelling skills through knowledge transfer.
· Automating data pipelines using proprietary BBC technology & Airflow.
· Using your expert knowledge of BBC products and their features to inform the design and development of data products and upskilling the team through this knowledge.
· Developing ways of working between product data domains and other data teams within product group.
· The creation of processes for data product development, ensuring these processes are documented and advocating their use throughout the organisation.
· Supporting analytics, data science and other colleagues outside the digital product area in managing projects and fielding queries.
· Ability to build and maintain strong working relationships where you might, as a specialist, have to manage the expectations of more senior colleagues.
· Working across mobile, web, television and voice platforms supporting Product Managers, Business Analysts and working closely with Software & Data Engineers.

Are you the right candidate

Technical Skills

• At least 5 years’ experience in a Data Analyst, Data Modelling, Data Engineering or Analytics Engineering role, preferably in digital products, with an interest in data modelling and ETL processes.
• At least 5 years experience in managing teams building data warehouses / analytics from a diverse set of data sources (including event streams, various forms of batch processing)
• Proven experience in dimensionally modelling complex data at the conceptual, logical and physical layer.
• Experience of designing STAR Schemas 
• Excellent SQL skills for extracting and manipulating data. Experience of using tools such as DBT, Looker and Airflow would be an advantage.
• Good knowledge of analytical database systems (Redshift, Snowflake, BigQuery).
• Comfortable working alongside cross-functional teams interacting with Product Managers, Engineers, Data Scientists, and Analysts.
• Knowledge of digital products and their components, as well as what metrics affect their performance.
• An understanding of how digital products use experimentation.
• Some experience coding in R or Python.
• A good understanding of on-demand audio and video media products, with a knowledge of key competitors

Teamwork and stakeholder management 


• 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. 
• Ability to prioritise. A structured approach and ability to bring other on the journey.
• Strong attention to detail

About the BBC


The BBC is committed to redeploying employees seeking suitable alternative employment within the BBC for different reasons and they will be given priority consideration ahead of other applicants. Priority consideration means for those employees seeking redeployment their application will be considered alongside anyone else at risk of redundancy, prior to any individuals being considered who are not at risk.

We don’t focus simply on what we do – we also care how we do it. Our values and the way we behave are important to us. Please make sure you’ve read about our values and behaviours here.

Diversity matters at the BBC. We have a working environment where we value and respect every individual's unique contribution, enabling all of our employees to thrive and achieve their full potential.

We want to attract the broadest range of talented people to be part of the BBC – whether that’s to contribute to our programming or our wide range of non-production roles. The more diverse our workforce, the better able we are to respond to and reflect our audiences in all their diversity.

We are committed to equality of opportunity and welcome applications from individuals, regardless of age, gender, ethnicity, disability, sexual orientation, gender identity, socio-economic background, religion and/or belief. We will consider flexible working requests for all roles, unless operational requirements prevent otherwise.

Get the latest insights and jobs direct. Sign up for our newsletter.

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

Industry Insights

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

Portfolio Projects That Get You Hired for Data Science Jobs (With Real GitHub Examples)

Data science is at the forefront of innovation, enabling organisations to turn vast amounts of data into actionable insights. Whether it’s building predictive models, performing exploratory analyses, or designing end-to-end machine learning solutions, data scientists are in high demand across every sector. But how can you stand out in a crowded job market? Alongside a solid CV, a well-curated data science portfolio often makes the difference between getting an interview and getting overlooked. In this comprehensive guide, we’ll explore: Why a data science portfolio is essential for job seekers. Selecting projects that align with your target data science roles. Real GitHub examples showcasing best practices. Actionable project ideas you can build right now. Best ways to present your projects and ensure recruiters can find them easily. By the end, you’ll be equipped to craft a compelling portfolio that proves your skills in a tangible way. And when you’re ready for your next career move, remember to upload your CV on DataScience-Jobs.co.uk so that your newly showcased work can be discovered by employers looking for exactly what you have to offer.

Data Science Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Data science has become one of the most sought‑after fields in technology, leveraging mathematics, statistics, machine learning, and programming to derive valuable insights from data. Organisations across every sector—finance, healthcare, retail, government—rely on data scientists to build predictive models, understand patterns, and shape strategy with data‑driven decisions. If you’re gearing up for a data science interview, expect a well‑rounded evaluation. Beyond statistics and algorithms, many roles also require data wrangling, visualisation, software engineering, and communication skills. Interviewers want to see if you can slice and dice messy datasets, design experiments, and scale ML models to production. In this guide, we’ll explore 30 real coding & system‑design questions commonly posed in data science interviews. You’ll find challenges ranging from algorithmic coding and statistical puzzle‑solving to the architectural side of building data science platforms in real‑world settings. By practising with these questions, you’ll gain the confidence and clarity needed to stand out among competitive candidates. And if you’re actively seeking data science opportunities in the UK, be sure to visit www.datascience-jobs.co.uk. It’s a comprehensive hub featuring junior, mid‑level, and senior data science vacancies—spanning start‑ups to FTSE 100 companies. Let’s dive into what you need to know.

Negotiating Your Data Science Job Offer: Equity, Bonuses & Perks Explained

Data science has rapidly evolved from a niche specialty to a cornerstone of strategic decision-making in virtually every industry—from finance and healthcare to retail, entertainment, and AI research. As a mid‑senior data scientist, you’re not just running predictive models or generating dashboards; you’re shaping business strategy, product innovation, and customer experiences. This level of influence is why employers are increasingly offering compensation packages that go beyond a baseline salary. Yet, many professionals still tend to focus almost exclusively on base pay when negotiating a new role. This can be a costly oversight. Companies vying for data science talent—especially in the UK, where demand often outstrips supply—routinely offer equity, bonuses, flexible work options, and professional development funds in addition to salary. Recognising these opportunities and effectively negotiating them can have a substantial impact on your total earnings and long-term career satisfaction. This guide explores every facet of negotiating a data science job offer—from understanding equity structures and bonus schemes to weighing crucial perks like remote work and ongoing skill development. By the end, you’ll be well-equipped to secure a holistic package aligned with your market value, your life goals, and the tremendous impact you bring to any organisation.