Analytics Engineer - Fully Remote in London

Location: London (Old Street office, 3 days/week). &##Join a high-growth, mission-driven tech company that’s transforming the future of work. &##We\’re not just closing the digital divide; we\’re reconnecting distributed organisations, enabling seamless communication, and re-engaging employees like never before. With teams in Boston, London, and Sydney, we\’re making waves worldwide, partnering with industry leaders like Domino’s, JD Sports and McDonald’s. We\’re passionate about data being at the core of our decision-making process. Our app allows us to collect data on everything from employee engagement and turnover to survey results, shift booking, and payslips. 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. 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. 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 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. 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. Competitive salary. ~ 25 days’ leave + public holidays. ~ Private healthcare with AXA. ~3% employer pension contribution when you contribute 5%. ~ Cycle to Work scheme. ~ Social events ( lunches, breakfasts, nights out)]] ~