Accepting applications until: 

Job Description

Your New Role: Lead Analytics Engineer

We're one of the largest media players in Europe, and data is at the heart of what we do. We capture data from our audio and digital channels, from our extensive outdoor business and beyond, and use this to create the best content for our audiences and an amazing experience for our clients.

The data team supports the whole company across all of these areas, and this scope gives us a rich array of data use cases to work on. These range from personalisation on our digital applications, to optimisation algorithms to allocate our inventory, to data for enabling operational excellence in our outdoor estate, generative technologies to develop ad creatives, and many others.

Three things set us apart:

• Distinctive problems to solve: As described above, we have some of the most diverse and rich data use cases for any media company. We're the only player to cut across audio, outdoor, digital, and to run a programmatic ad exchange

• Unique data sets: In line with the above, we have some truly unique data sets to work with - and at large scale. This includes our front-end data, data from our ad exchange, outdoor operational data, audio listening data, and much more. It also includes some unique data partnerships: for example, we have access to unique data on travel movements for the TfL network in London

• Scale: We're a privately-owned, mid-cap business, with a long-term perspective. We have the flexibility, pace, and opportunity to work on big problems that an early-stage business would. But equally, we have the scale to make an impact on millions of consumers, and the big data volumes you'd expect of a large business

We're looking for a Lead Analytics Engineer to guide a team of analytics engineers to scale our data modelling capabilities, manage data pipelines, and empower stakeholders across Global with high-quality, trusted data.

Key Responsibilities

• Team Leadership & Development (30%): Lead, coach, and support a team of analytics engineers. You'll ensure personal growth, professional development, and consistent performance across your team by setting clear goals and fostering a collaborative, inclusive environment.

• Data Modelling and Transformation (30%): Design, implement, and oversee scalable data models with a focus on reusable data assets that can deliver value across multiple use cases. You'll drive consistency and quality in how data is structured and documented, enabling downstream analytics and decision-making.

• Data Pipelines & Processes (20%): Own and optimise the data pipelines and engineering workflows. Through engineering best practices inc automated testing you'll maintain data accuracy, performance, and operational integrity across the development lifecycle.

• Cross-functional Collaboration & Strategy (20%): Work closely with data analysts, scientists, product managers, and business stakeholders to align engineering work with business goals. You'll help define and execute the vision for Global's analytics platform.

What You'll Love About This Role

Think Big: Be a strategic leader driving the evolution of our analytics infrastructure at scale. Own It: Lead initiatives from design to implementation, delivering real business impact through data. Keep it Simple: Build clear, documented models that make data intuitive and easy to use for all stakeholders. Better Together: Mentor your team and partner cross-functionally to create a culture of excellence and collaboration.

What Success Looks Like

In your first few months, you'll have:

• Built trust and alignment across your team and cross-functional stakeholders.

• Delivered critical data models in dbt and Snowflake to support key business initiatives.

• Introduced standards and frameworks for analytics engineering best practices.

• Supported the career development of your team members with clear, actionable feedback and mentorship.

• Elevated team performance through strong leadership and a culture of ownership.

What You'll Need

• Data Modelling: Proven ability to design and maintain scalable, well-documented data models that enable multiple use cases.

• Expertise in dbt: You know dbt inside out and can design scalable, modular data models that follow best practices.  Knowledge of other tools e.g. SQL Mesh a bonus.

• Strong SQL and Snowflake Knowledge: You are proficient in writing complex SQL and have experience with Snowflake architecture and optimisation.

• Orchestration: Proficiency with orchestration tools (E.g. Airflow)

• DataOps: Experience with git & CI/CD, and familiarity with good FinOps practices

• Problem Solver: You enjoy digging into ambiguous problems and designing elegant, scalable solutions.

• Collaboration & Communication: You can translate technical data concepts into language non-technical stakeholders understand.

• Coaching and Development: Nurturing talent by empowering and guiding individuals to unlock their potential

• Building Trust: Creating and maintaining an inclusive environment where diverse views and experiences are welcomed and celebrated in your team