Global Logo

Global

Analytics Engineer

Posted 2 Days Ago
Be an Early Applicant
In-Office
Holborn-Strand-Covent Garden, London, England, GBR
Entry level
In-Office
Holborn-Strand-Covent Garden, London, England, GBR
Entry level
Build and maintain scalable data models and curated datasets for analytics, BI, product, and data science. Apply consistent business logic, define metrics, implement automated data quality tests, and document data assets. Partner with Data Engineering, Analytics, Product, Data Science, and commercial stakeholders to align KPIs and support decision-making. Use Snowflake, dbt, Airflow, Python, SQL, cloud services, Git, CI/CD, and Agile practices.
The summary above was generated by AI
Accepting applications until: 9 October 2026Job 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

In your first few months, you’ll have:

  • 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’ goalsWorked 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)
    • DataOps: Experience with git & CI/CD, and appreciation of FinOps
    • Cloud: Proficiency with cloud services (ideally AWS)
  • Agile ways of working: Understanding of Agile methodologies and experience of using Jira
  • Can do attitude: Proactive, problem-solving attitude with strong attention to detail
  • To be organised: Strong organisational skills with the ability to work both individually or part of a team and an eye for detail and quality
  • Great communication: An ability to break down and explain sophisticated technical concepts to business end users
  • A growth mindset: A proven ability to learn new skills and pick up new technologies quickly

Creating a place we all belong at Global We are dedicated to creating a place where different voices are represented, amplified and celebrated. We know that we can’t serve our diverse audiences without first celebrating it in our people, which is why we’re passionate about creating an inclusive culture where every Globaller can belong. So, no matter who you are or where you are from, you can find your place at Global.  As a business, we believe in the importance of a healthy work-life balance and the value of a flexible and agile workforce. Therefore, we operate a Smart Working approach. If you need us to make any reasonable adjustments during your recruitment process, drop us an email at [email protected], we’ll be happy to help.

HQ

Global London, England Office

30 Leicester Square, London, United Kingdom, WC2H 7LA

Similar Jobs

5 Hours Ago
In-Office
London, Greater London, England, GBR
Entry level
Entry level
Financial Services
Design and own dbt-based transformation layers that convert raw operational data into reliable, documented analytical assets. Build tested data models, semantic layers, metrics, and entities supporting dashboards and self-service analytics. Collaborate with engineers, analysts, and stakeholders to translate requirements into production data products. Use SQL, Python, Git, CI/CD, and AI coding tools to accelerate delivery while maintaining testing and human oversight. Review peer work and maintain models through schema changes and user feedback.
Top Skills: Ci/CdClaude CodeCodexCursorDbtGitLookmlPythonSQL
7 Days Ago
Hybrid
Entry level
Entry level
Insurance
Develop and maintain Power BI, paginated reporting, semantic models, datasets, and Databricks analytics solutions. Translate stakeholder needs into reliable insights, improve performance, validate data, document solutions, and support migration from legacy reporting platforms. Collaborate in Agile cross-functional teams, follow modeling, testing, deployment, and version-control standards, manage assigned work, communicate assumptions and risks, and contribute to continuous improvement and automation.
Top Skills: Ai-Assisted Development ToolsAzure DevopsCopilotsDatabricksDaxGitPower BISQLTabular Editor
8 Days Ago
Hybrid
London, Greater London, England, GBR
Entry level
Entry level
Fintech • Payments • Financial Services
Build and improve analytical data models supporting lending decisions, pricing, portfolio analysis, and investor reporting. Develop scalable ELT transformations, strengthen data quality and reliability, support analysts, troubleshoot pipeline issues, and improve transformation efficiency and cost-effectiveness. Collaborate with product, engineering, analytics, and business stakeholders while promoting analytics engineering standards and effective use of AI tools.
Top Skills: ClaudeDbtFivetranSnowflakeSQL

What you need to know about the London Tech Scene

London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account