Senior Data Analyst — PropTech / Block Management Roll-Up
London-commutable / Hybrid
c£75k + bonus + share options
This is the UK's first AI-enabled roll-up of property service companies. Backed by leading VCs and founded by the team behind one of the UK's largest digital property managers, the business acquires excellent owner-operated companies and transforms them into a modern, technology-enabled group using AI.
Every business they acquire brings its own data - different systems, different standards, different levels of rigour. Making sense of that, and turning it into something useful, is one of the most important things to do.
THE ROLE
This is an analyst role, not an engineering role. The centre of gravity is insight - finding patterns in operational data, understanding what they mean for how a business runs, and communicating that clearly to operators and leadership who are not data specialists.
You will work across a portfolio of acquired businesses simultaneously, largely independently. There is no large team around you and no fully specced brief on your desk. You need to be the kind of analyst who looks at a dataset and gets curious about what is wrong with it, what it is hiding, and what it is trying to tell you.
WHAT YOU'LL BE DOING
Analysis and Insight
– Explore operational data across acquired businesses to find patterns, inefficiencies, and improvement opportunities
– Turn what you find into clear, actionable insight for operators and leadership - not dashboards that nobody reads, but conclusions that change decisions
– Put AI tooling to work on analysis, reconciliation, and anomaly-spotting at scale
Inbound Data Quality
– Own QA on inbound data from newly acquired companies - profiling, reconciliation, validation against source, anomaly detection
– Develop the instinct for where data is wrong before it reaches our systems, not after
– Use AI tooling to strengthen and accelerate validation
Internal Data Products
– Partner with engineering and internal users to shape data products - defining metrics, clarifying requirements, validating that outputs are correct and useful
– Be the analytical voice in product conversations, translating operational reality into data model requirements
ETL Support
– Contribute to transformation logic, source-to-target mappings, and data preparation alongside the engineering team
– You won't own pipelines end to end - but you'll understand them well enough to shape what goes in and check what comes out
ABOUT YOU
– Strong analytical background - analyst, BI, or data science roles where insight drove decisions, not just dashboards
– SQL and spreadsheets at a high level; comfortable interrogating and reconciling data rather than taking it on trust
– Experience doing real data QA - profiling, validation, reconciliation, anomaly detection - with an instinct for where data goes wrong
– Comfortable partnering with engineering on internal tooling: metric definition, requirements, output validation
– Resourceful with AI tooling - knows how to use LLMs to accelerate analysis and validation work
– Some ETL exposure: transformation logic, mappings, data preparation - you don't need to own pipelines, but you need to understand them
– Experience working solo or in small teams across multiple workstreams; consulting or contracting background is a plus
– Able to communicate findings clearly to non-technical operators - insight that stays in a notebook doesn't count
This role is not right for pure data engineers with no analytical instinct, analysts who take data at face value, or people who need a fully-defined brief before they can start.
WHY JOIN
– A pivotal early hire in the data function of one of the UK's most ambitious AI-PropTech startups
– Real breadth - working across multiple businesses, asset types and operational challenges simultaneously
– High autonomy and direct exposure to leadership
– Competitive salary, bonus and share options
– A company where the work you do is visible and the impact is immediate
Requirements added by the job poster
• 5+ years of work experience with Data Quality
