Analytics Engineer

Job Description

As our first dedicated data engineer, you will be the bridge between data infrastructure and analytics. You’ll own how raw data is turned into trusted, well-modelled datasets that power decision-making. This means building and optimising dbt models, defining core business metrics, establishing data quality standards and collaborating closely with our BI team and stakeholders

Initially, it’s likely you’ll own these things end-to-end, but over time we’ll build a team around you. While your focus is the modelling layer, this is a scaleup environment and you'll need to be versatile - comfortable influencing upstream data design and pragmatically solving problems across the data stack

Build, maintain, and optimize data transformations, models, and pipelines in dbt (or equivalent) - including testing, documentation, and version control

Define, own, and monitor business metrics and models (e.g. dimension tables, slowly changing dimensions, aggregates)

Collaborate with analysts, BI users, data scientists, and business stakeholders to translate data requirements into reliable data products (tables, views, metrics)

Ensure data quality, consistency, and observability (tests, monitoring, alerting)

Optimize SQL queries and transformations for performance in your data warehouse / lakehouse environment

Support or own CI/CD workflows around analytics (e.g. git, reviews, deployment of transformation code)

Build or maintain upstream data pipelines or ingestion processes when required

Who you are

• Strong proficiency in SQL - writing and optimizing complex queries, joins, window functions, performance tuning
• Experience with dbt (or equivalent) - building models, tests, documentation, version control
• Understanding of data warehousing concepts (star schemas, snowflake, slowly changing dimensions, partitioning, clustering)
• Experience working in a modern data stack (e.g. BigQuery, Snowflake, Redshift, Databricks, etc.)
• Comfortable working downstream (with BI/analytics users) and upstream (pipelines, ingestion) contexts
• Familiarity with BI tools (we use Thoughtspot and Power BI)
• Proficient in Python
• Solid software engineering skills, including version control, testing, and CI/CD
• Versatile and adaptable - comfortable working across the stack and able to rapidly learn new tools and solve novel problems
• You are a great communicator, equally comfortable engaging with technical and non-technical stakeholders
• Experience in a lean or startup environment is a plus

Company Benefits

• Generous equity allocations with significant upside potential
• All the traditional benefits such as Health Insurance (AXA Health), Ride2Work and Pension schemes
• Ability to grow, learn and solve a variety of challenges, working in a supportive environment with smart, driven people
• Office fridge filled with snacks and drinks, regular team lunches and socials
• The opportunity to be part of something impactful, large-scale, meaningful & fulfilling
• 25 days holiday (excl. bank holidays)