Senior Data & Analytics Engineer

As a Senior Analytics Engineer, you’ll work as part of a multi-disciplinary, agile data delivery team, contributing to the build and evolution of analytics-ready data across our platform. This role is analytics engineering first, with a strong emphasis on implementing and maintaining complex models in our Silver and Gold data layers, rather than defining modelling strategy from scratch.

You’ll join a multi-disciplinary, agile data delivery team working alongside other analytics and data engineers, data scientists, test engineers, and data visualisation specialists.

What’s in it for you?

• Remote working
• Annual pay reviews
• A generous discretionary profit-share scheme
• The opportunity to work with a modern data stack and shape analytics at scale

What you’ll be doing As a Senior Analytics Engineer, you’ll focus primarily on the analytics layer of the platform, while working closely with data engineering colleagues on upstream ingestion and orchestration., * Building and maintaining analytics-ready data models in our cloud data warehouse, transforming raw and curated data into trusted, well-documented datasets for business and analytical use

• Implementing complex data models and transformations using SQL and dbt, with a strong understanding of how upstream transformations feed downstream analytical use cases
• Working with existing enterprise data models and dimensional structures, confidently navigating and extending them to support new analytics requirements
• Owning and contributing to the enterprise data warehouse, including dimensional models and analytical data sets that serve both technical users and non-technical business stakeholders
• Collaborating with data engineers on the ingestion and orchestration of data from a wide range of sources (databases, flat files, APIs, and event-driven feeds), ensuring downstream analytics requirements are considered early
• Working closely with analytics, data science, and visualisation teams to ensure data products are fit for purpose, performant, and trusted

• Supporting production data assets, including monitoring, issue resolution, and continuous improvement Helping drive a data-first culture, contributing to data enablement activities, analytics best practices, and knowledge sharing across the data community

• Acting as a senior technical contributor within the team, influencing standards, patterns, and ways of working

What you’ll bring We’re looking for someone who is analytics-engineering-led, with enough data engineering experience to work confidently across the full data lifecycle.

• Strong experience building and maintaining analytics pipelines using SQL-first transformation patterns, ideally with dbt
• Solid understanding of data warehousing concepts, including how dimensional and analytical models are used downstream, without requiring deep ownership of modelling design decisions
• Advanced SQL skills, with the ability to write, read, and optimise complex queries across large datasets
• Experience working with a cloud data warehouse such as Snowflake (preferred), BigQuery, Redshift, or Synapse
• Experience working in a modern cloud environment (AWS, GCP, or Azure), with exposure to core services such as cloud storage and orchestration
• Experience working in an Agile delivery environment (Scrum and/or Kanban), with strong communication skills and the confidence to work directly with stakeholders at all levels, * Experience contributing to or supporting data ingestion pipelines, including APIs and event-driven data sources
• Familiarity with orchestration tools (e.g. Airflow) and ELT architectures
• Experience implementing or working with data CI/CD pipelines (for example, dbt tests, deployment pipelines, or automated checks). We currently use Azure DevOps
• Working knowledge of Python for data-related tasks, automation, or light engineering work
• An interest in data quality, observability, and analytics engineering best practices

Why this role is different This is not a pure platform data engineering role, nor is it a purely reporting-focused analytics role. It’s an opportunity to:

• Own and shape the analytics layer that the business relies on
• Apply modern analytics engineering practices at scale
• Work with a contemporary stack: AWS, Snowflake, dbt, Airflow, SQL, and Python
• Influence how data is modelled, trusted, and used across the organisation