Analytics Engineer

This is an opportunity to join a growing data function where analytics sits at the heart of business decision-making. You'll take ownership of a critical data layer, work with modern cloud technologies, and play a key role in scaling analytics capabilities across an international organisation.

The Company

They are a well-established and innovative organisation with a strong digital presence and a commitment to data-driven decision making. Operating at scale across multiple markets, they continue to invest heavily in their data and analytics capabilities.

Their teams work closely with stakeholders across commercial, product, marketing, and operational functions to deliver meaningful insights and business value. As they continue to mature their data platform, they are looking for an Analytics Engineer to help shape best practices and support future growth.

The Role

You will be responsible for building and maintaining the core analytics data models that underpin reporting, self-service analytics, and wider data initiatives.

Responsibilities include:

• Designing, developing, and maintaining analytics and reporting data models using dbt and BigQuery
• Creating scalable, high-quality datasets that support business reporting and decision-making
• Developing and maintaining data pipelines and workflows
• Implementing testing, monitoring, and documentation standards to improve data quality and reliability
• Working closely with analysts, engineers, and business stakeholders to understand requirements and deliver data solutions
• Supporting and enhancing Looker reporting capabilities and self-service analytics
• Managing upstream dependencies and helping establish strong data governance practices
• Driving continuous improvements across data modelling, automation, performance, and deployment processes

Your Skills & Experience

• Strong commercial experience in Analytics Engineering, Data Engineering, or Business Intelligence development
• Advanced SQL skills with a focus on performance and optimisation
• Hands-on experience with dbt, including modelling, testing, and documentation
• Experience working with Google BigQuery in production environments
• Python experience for data processing, automation, or analytics workflows
• Experience building and maintaining pipelines using Airflow or similar orchestration tools
• Strong understanding of dimensional data modelling and analytics best practices
• Experience supporting BI and reporting platforms such as Looker
• Ability to communicate effectively with both technical and non-technical stakeholders
• A quality-focused approach to testing, documentation, and data governance