Principal Analytics Platform Engineer

Overview

Job Description

Responsibilities

• - Own the end-to-end analytics platform vision: Define the architecture, tooling choices, and standards the data team builds against, combining data engineering, analytics engineering, and BI delivery into a single cohesive strategy
• - Work through domain experts, not around them: Partner closely with data engineers, analytics engineers, and analysts to translate that vision into execution, enabling them to go deep in their specialisms rather than doing it all yourself
• - Build the analytics foundations the business can rely on: Establish repeatable analysis patterns, metric definitions, testing standards, and the semantic layer, so teams across the company are working from a shared, trusted view of the business
• - Transform data access: Design scalable self-serve patterns and explore new approaches to data consumption, from dashboards and embedded analytics to direct tool integrations, so teams can get what they need without raising an ad hoc request
• - Elevate analytics from a reporting function to a strategic partner: Introduce causal analytics, advanced analytics, and data science approaches that help the business understand not just what happened, but why, and what to do next
• - Bridge data strategy to business outcomes: Act as the primary connection between the data service and the rest of the business, translating business need into data priorities and data strategy into language the C-suite can act on
• - Keep the platform ahead of the curve: Continuously evaluate new approaches to analytics delivery, curious about how the field is evolving and willing to introduce those advances in ways that reduce strain on the team

Required Skills

• - Exceptional communicator: Equally at home with technical ICs and with the C-suite, can translate fluently between the two and make data strategy legible to anyone in the room
• - Full-stack analytics depth: Hands-on understanding of the modern analytics stack, from ingestion and warehouse architecture through transformation (dbt), semantic layers, and BI delivery; the kind that comes from having built and operated each layer, not just having opinions about them
• - Data standards that stick: A track record of establishing analytics standards the business actually adopted, repeatable analysis patterns, metric definitions, modeling conventions, data quality frameworks, and the communication skills to drive that adoption
• - Self-serve data access experience: Has built or designed scalable data access capabilities, semantic layers, BI tooling, embedded analytics, or equivalent, and understands what makes them succeed or fail
• - A clear POV on what good looks like: Can assess current state, identify the gaps, and articulate a credible roadmap without waiting for someone to define the destination
• - Startup experience that counts: Demonstrable experience navigating analytics challenges at an early-stage company, has been in the messy early phase, knows what failure looks like, and has built a way out of it

Benefits

• - Competitive salary - our current band for this role is £130,000 or equivalent in local currency. We review salaries twice a year using real-time market data, with transparent, consistent pay for the same role and level.
• - Stock Options - everyone on the team has ownership in our mission.
• - 25 days holiday + public holidays - Swap public holidays for ones that matter most to you. Plus, get an extra day off for your birthday 🎉.
• - Remote & flexible working - We're fully remote, distributed across Europe with clear core hours, and no internal meetings on Friday afternoons.
• - Home working & wellbeing budgets: Up to £1,200 / €1,200 annually to upgrade your remote setup (co-working passes, equipment, etc.). Up to £150 / €150 monthly on anything that supports your wellbeing - from therapy to gym memberships to meditation apps.