Senior Data Engineer

About the Role

We are hiring Data Engineers at all levels, seeking individuals who bring deep technical expertise and a clear drive to deliver measurable results.

In this role, you will lead end-to-end engineering projects, designing and building the scalable data infrastructure that underpins our business. From architecting data lakes and developing customer data platforms to delivering AI-powered intelligence solutions, you will play a central role in creating the analytical data products and foundational systems that enable data-driven decisions across multiple business lines.

This is a compelling opportunity to shape high-impact projects, work alongside senior leadership, and make a meaningful contribution to our core media business.

Roles & Responsibilities

Data Infrastructure & Architecture

• Design, build, and maintain scalable data pipelines and lake architectures that serve as the backbone of audience, product, and commercial decision-making across the organisation
• Architect and manage our data lake ecosystem, defining standards for data ingestion, storage, transformation, and access across structured and unstructured data sources
• Contribute to the evolution of our data stack, evaluating and implementing tools and technologies that improve performance, scalability, and developer experience
• Design and maintain a feature registry that serves as the single source of truth for cataloguing, lineage, ownership, and SLAs; supports Data Scientists and Machine Learning Engineers with robust search, documentation, and discovery capabilities across a large feature portfolio

Data Products & Platforms

• Develop and own core data products including our customer data platform, audience intelligence and other AI-powered analytical tools, ensuring they are reliable, well-documented, and built for scale
• Build and maintain robust data models that support analytics, reporting, and machine learning use cases across multiple business lines including subscriptions, advertising, and editorial

Governance & Quality

• Establish and champion data quality standards, governance frameworks, and observability practices that ensure trust and reliability in our data across the organisation

AI & Advanced Analytics

• Partner with Data Scientists, Machine Learning Engineers, and Product teams to co-develop and deploy AI-powered solutions that drive audience growth and engagement
• Translate complex and ambiguous business requirements into well-scoped, production-grade data solutions that can operate reliably at scale in a fast-moving media environment

Capability & Knowledge Development

• Stay abreast of the latest developments in data engineering and AI, evaluating their practical applicability to our business context
• Contribute to a culture of technical excellence, knowledge sharing, and continuous improvement across the data organisation

Who are we looking for

Educational Qualifications

• An advanced degree(Master's or PhD) in Computer Science, Computer Engineering, Data Engineering, or a related quantitative field
• Candidates without a formal advanced degree who can demonstrate equivalent depth through a strong professional track record and portfolio of impactful work are equally encouraged to apply

Technical Experience

Data Products & Platforms

• Minimum 8 years of hands-on experience designing and building dataproducts such as customer data platforms, audience analytics platforms, orpersonalisation and recommendation systems
• Proven ability to deliver data products that are reliable,well-documented, and built for scale in a production environment
• Experience building AI-powered solutions, including integration withmachine learning models and intelligent data pipelines, will be highly regarded
• Experience in the media or internet industry is a strong advantage

Data Infrastructure& Architecture

• Hands-on experience architecting and maintaining data lake ecosystems, defining standards for data ingestion, storage, transformation, and access across structured and unstructured data sources
• Demonstrated experience building and managing low-latency large-scale data pipelines that serve analytics, reporting, and machine learning use cases
• Experience in designing, building and operating centralised feature store, with an emphasis on consistency, correctness and reusability between training and serving environments
• Strong proficiency with large-scale batch and streamlining data processing frameworks, and applying them in production environments

Analytics Engineering

• Experience with analytics engineering practices and tools, including data modelling, transformation layer design, and documentation standards
• Strong understanding of data warehousing concepts, dimensional modelling, and modern lake house architectures

Core Engineering Skills

• Deep proficiency in SQL, Apache Spark and at least one programming language such as Python or Scala. Coding tests may be required.
• Solid understanding of data governance best practices, data quality frameworks, and observability tooling

Functional Skills

• Minimum 10 years of experience building and managing high-performance engineering teams, with a track record of fostering technical excellence, accountability, and a strong culture of delivery
• Excellent communication skills with the ability to translate complex technical concepts for both technical and non-technical stakeholders across product, editorial, and commercial teams
• Comfortable working in cross-functional, fast-moving environments where priorities may evolve