Analytics Engineer in London

Accepting applications until

9 October 2026

Job Description

• Analytics Engineer
• We are Global

At Global, we think big, work hard, and never stand still.

We're the proud home of the best media and entertainment, driven by our talented and passionate people.

Our mission?

To make everyone's day brighter - our Globallers, our audiences, our partners, and our communities.

Whether we're in the studio, building world-class technology, or securing record Outdoor advertising partnerships, we make sure we're doing it as a team.

Your Role: Analytics Engineer

As an Analytics Engineer at Global, you will be part of the Data team, providing Analytics Engineering expertise across the business to build new data products and drive key decision making.

You will be instrumental in building datasets and applying the relevant business logic that can be used by Analysts and collaborators.

The Analytics Engineer will work closely with both the Data Engineering and Analytics team.

They will need to apply business logic to the datasets being created alongside the Analytics team and ensure best practices are followed with Data Engineering.

The Analytics Engineer will be expected to transform data so that it can be used by many different users such as Business Intelligence, Data Science and Analysts, ensuring they are all aligned on definitions and metrics.

Key Responsibilities

• Data modelling & product development (50%)
• Design, build and maintain scalable, reusable and well-documented data models to support analytics, BI, product and data science use cases.
• Transform complex raw and intermediate data into curated datasets that are easy to use and aligned to business needs.
• Apply business logic carefully and consistently to ensure data products are trusted and fit for purpose.
• Develop reusable semantic layers, metrics and core entities that support multiple downstream use cases.
• Work with Data Engineering to ensure source data structures and transformations support high-quality analytics outputs.
• Data quality, testing & documentation (25%)
• Build rigorous automated checks to ensure freshness, completeness, consistency and accuracy of datasets.
• Establish testing standards for analytics models, including schema, business rule and metric validation.
• Create and maintain clear documentation so users can quickly understand datasets, definitions and intended use cases.
• Improve discoverability and usability of data assets across the Global environment.
• Business partnership & metric definition (25%)
• Partner with Analytics, Product, Data Science and commercial stakeholders to understand requirements and translate them into robust data models.
• Align stakeholders on common definitions, KPIs and business logic across audience, campaign and measurement use cases.
• Support decision-making by ensuring analytical datasets reflect the right level of business context and domain understanding.
• Identify strategic opportunities where analytics engineering can improve insight generation, consistency and speed to value.
• What You'll Love About This Role
• Think Big : We've got some of the largest and most diverse data sets in UK media - with scale that continues to grow. You'll play a role in harnessing the value in that data.
• Own It : You'll be doing this by gaining expertise in one of our data domains
• Keep it Simple : With a focus on reusability of data sets and models to support multiple use cases
• Better Together : You'll be working in a team with kind, supportive people that look out for you and help you to do the best work that you can.

We put a lot of energy into our team culture and ensuring that everyone is fulfilled with their work.

• What Success Looks Like
• Learnt how the team operates and uses technologies such as Snowflake, dbt, Airflow
• Built a clear understanding of the strategic direction of Data and Analytics at Global as well as how these feed into the wider business' goals Worked with the Data Engineering and Analytics teams to structure datasets that can be used to build data products and other use cases depending on stakeholder briefs
• Integrated within Agile team ceremonies such as daily stand ups, retrospectives and backlog refinements
• Started to establish a strong understanding of Global's datasets and their use in the business
• What You'll Need
• Analytics
• Engineering

Skills: previous experience in an Analytics Engineering position Data Modelling : Proven ability to design and maintain scalable, well-documented data models that enable multiple use cases.

• Data Curation Tools: e. g. dbt or Python for data manipulation and transformation
• SQL: ability to write complex SQL that runs efficiently especially on cloud data platforms (E. g. Snowflake)
• Orchestration: Proficiency with orchestration tools (E. g. Airflow)
• Data
• Ops: Experience with git & CI/CD, and appreciation of Fin Ops
• Cloud: Proficiency with cloud services (ideally AWS)
• Agile ways of working: Understanding of Agile methodologies and experience of u
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