Analytics Engineer

Location: London, Hybrid [1-2 days per week on site]  

Our Team: How we enrich everyday life 

You’ll be joining our Data & Decision Sciences (DDS) team at Bauer Media Audio, where we use data to power decisions across nine European markets. We’re a collaborative, cross-functional team working across commercial revenue, digital audiences, and consumer competitions, turning complex data into insights that shape how millions of people engage with our brands every day.  

Working closely with Data Engineers, Data Scientists, Product Managers and business stakeholders, we combine central expertise with local market knowledge to deliver real impact. 

The difference you will make 

As an Analytics Engineer, you’ll play a key role in transforming raw data into trusted, business-ready insights. You’ll help build the data models and semantic layers that underpin reporting and analytics across Bauer Media Audio, enabling teams to make smarter, faster decisions.  

This is an exciting opportunity to help modernise our data platform, working with emerging technologies and shaping how data is structured, defined, and consumed across the business. 

Your role 

You’ll design and build scalable data models and pipelines that translate complex data into meaningful insights for the business. 

Responsibilities include, but are not limited to: 

• Design and develop dimensional data models and marts using dbt and Kimball principles


• Build and maintain transformation pipelines from raw data to business-ready datasets


• Define and evolve semantic layers to ensure consistent metrics and reporting across tools like Looker, Power BI and Tableau


• Collaborate with Data Engineers to shape upstream data and improve data pipelines


• Implement data quality checks and maintain reliable, trusted datasets


• Support the migration and modernisation of legacy data platforms to Snowflake


• Maintain documentation including data dictionaries and semantic definitions


• Contribute to agile workflows, code reviews, and cross-functional collaboration


• Get involved with setting up Airflow DAGs or write Terraform to setup infrastructure.  

The skills you will bring 

Must-have: 

• Strong SQL skills and experience with modern cloud data warehouses (e.g. Snowflake, Redshift, or BigQuery)


• Hands-on experience with dbt for data transformation and modelling


• Solid understanding of dimensional modelling (Kimball methodology)


• Experience working with BI tools such as Looker or Power BI


• Comfort working in agile teams using tools like Jira and GitHub


• Strong communication skills with the ability to translate data into business concepts 

Nice-to-have: 

• Experience with Snowflake or modern cloud data platforms


• Exposure to Airflow, Terraform, or CI/CD practices


• Experience with data quality tools such as Great Expectations


• Familiarity with Tableau or multi-BI environments


• Background in media, digital, or subscription-based businesses


• Experience using Python for data and analytics engineering tasks