Staff Analytics Engineer

Job not on LinkedIn

🔥 12 hours ago

🇬🇧 United Kingdom – Remote

💵 £115k / year

⏰ Full Time

🔴 Lead

📊 Analytics Engineer

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tem

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2021

⚡ Energy

🛍️ eCommerce

☁️ SaaS

Energy • eCommerce • SaaS

tem is a company that empowers businesses to save on energy costs by directly purchasing from renewable energy generators. With its innovative RED™ product, tem simplifies the energy procurement process, offering transparency and a streamlined portal for managing contracts, quotes, and billing. The company aims to reduce the expense associated with traditional energy suppliers, enabling clients to cut energy costs by up to 25% while supporting the transition to renewable energy. tem's mission is to create accessible renewable energy solutions for all businesses, promoting sustainability and fair pricing within the energy market.

📋 Description

• Set and raise the bar on analytics engineering standards. Define the patterns, testing, and review practices that keep dbt models across the business consistent, documented, and trustworthy without you personally checking every one. • Own the context layer. Bring the semantic layer (Omni) and the underlying domain models together into one place the business, human or AI, can query with confidence. • Build the domain model from first principles. Take tem's data from raw source to a structured, trusted layer that powers commercial, financial, risk, and operational decisions, not just dashboards. • Expand analytics engineering's reach across the business. Integrate new data sources, product and platform events, and the tools other departments run on, taking analytics engineering from a centralised function into new corners of the company. • Help tem think bigger. As the business looks at big bets like international expansion and new ways of bringing its technology to other companies, help build a domain layer that's ready to go with it. • Partner across the business, not just the data team. Work directly with engineers, product managers, and salespeople to understand what they're actually trying to achieve, then turn that into models that hold up under real use.

🎯 Requirements

• You've built or reworked a domain layer before, hit the failure states, and learned what good looks like the hard way. • Deep, production dbt experience: custom macros, reusable patterns, and real work optimising models that are genuinely expensive to run. • Excellent SQL and comfort working on a modern data warehouse at real scale (tem runs ClickHouse). • Hands-on experience with a semantic layer or BI modelling tool (Omni, Looker, or similar), with genuine influence over how metrics get defined, not just how they get built. • A genuine eye for detail and real QA discipline: you check your own work and care about getting a definition right without needing someone else to catch it, while still keeping pace with a fast-moving business. • Experience with commercial data, like sales funnels or CRM pipelines, or with portfolio and financial trading data, including risk, hedging, forecasting, or time-series modelling. • A track record of introducing quality standards or tooling that measurably raised a team's output, not just your own. • Strong first-principles stakeholder management: you'd rather ask the awkward scoping question upfront than build the wrong thing twice. • Experience in energy, or another sector with real physical or financial complexity underneath the data.

🏖️ Benefits

• Offers Equity