About the role

RevOps Data Engineer responsible for building and maintaining revenue data for HX's growth across marketing and sales. Transforming complex data into actionable insights for decision-making.

Responsibilities

Model core revenue metrics (ARR, NRR, pipeline, win rate, velocity, retention) into a single source of truth that's easy to use and hard to misinterpret, with clear definitions and ownership.
Build and maintain the executive and board revenue dashboards leaders rely on, and publish a certified metrics layer so the wider team can self-serve with confidence.
Turn business rules into operational signals and ship them into our GTM systems (intent scores, routing priority, expansion propensity, etc.) so humans and AI automations can act on them.
Join CRM, marketing, product, and billing data into clean, trusted views, handling company and contact deduplication, identity stitching, and enrichment, then keep it fresh daily (hourly where needed) with sensible alerts and fast recovery plans.
Treat analytics like software: work in SQL and Python with Git and pull requests, clear definitions, thoughtful change control, and comprehensive runbooks.
Use AI to go faster on tests, documentation, and anomaly checks. Always verifying outputs before anything ships.

Built and maintained dashboards and KPI definitions (ARR, NRR, pipeline, conversion, retention), reconciled them with other departments, and created documentation so others can self-serve confidently. Used AI to accelerate analysis while verifying outputs.
Integrated data from multiple commercial systems (CRM, billing, product events, marketing) into a coherent model, implemented deterministic deduplication and hierarchies, and handled schema changes gracefully.
Treated analytics like software: strong SQL and practical Python (pandas), Git and pull requests, dev-to-prod workflows, validation tests, runbooks, and reproducible notebooks.
Translated commercial requirements into operational outputs (reverse-syncs, APIs, exports) that humans and AI agents consume (routing bots, campaign triggers, automations), and demonstrated measurable business impact.
Partnered with commercial teams to solve data problems that led to real business outcomes - not just building ad hoc analyses, but creating repeatable data flows that pushed trusted data into business systems.
Owned data flows end-to-end from source to dashboard or signal, including scheduling, monitoring, sensible alerts, and recovery plans that meet SLAs.

£5,000 training and conference budget for individual and group development.
25 days of holiday plus 8 bank holidays (33 days total).
Company pension scheme via Penfold.
Mental health support and therapy via Spectrum.life.
Individual wellbeing allowance via Juno.
Private healthcare insurance through AXA.
Income protection and Life Insurance.
Cycle to Work Scheme.
Top-spec equipment (laptop, screens, adjustable desks, etc.).
Regular remote and in-person hackathons, lunch and learns, socials, and game nights.
Team breakfasts and lunches, snacks, drinks fridge, and a fun office at The Ministry.
Access to cutting-edge AI tools and experimentation budget, giving you the freedom to test, learn, and innovate ahead of the market.
Exceptional opportunities for personal development and growth as we build something remarkable together.