UpGuard - Analytics Engineer

• Proven Craft: 5+ years building and owning analytics engineering or modeling work, with significant time spent on Revenue, Sales, or Customer Success domains within a B2B SaaS company. • Revenue Domain Expertise: Deep familiarity with B2B SaaS revenue schemas – ARR, bookings, pipeline, opportunity lifecycle, churn, expansion, contraction, NRR, GRR – and the practical messiness of how these metrics are calculated and reconciled in a real business. • CRM Experience: Strong, hands-on experience modeling data from HubSpot and/or Salesforce. You know where the bodies are buried – object relationships, history tables, the difference between what the CRM says and what reality is – and you can navigate it. • Requirements Translation: A demonstrated ability to take loose, ambiguous, or evolving requirements and turn them into well-structured dbt models, clear metric definitions, and outputs stakeholders can act on without needing to ask follow-up questions. • 80/20 Judgement – and the Discipline to Build Properly: You can ship a sharp answer quickly when speed matters, and you can build a durable, governed data product when the situation demands it. You know which one you’re doing and why, and you can defend the call. • Commercial Acumen: Strong commercial instincts – you understand why the business cares about a metric before you build it, and your models reflect commercial reality, not just schema convenience. • Attention to Detail: Genuinely meticulous. You reconcile, you test, you document, you check the edges. You don’t ship a revenue model and find out it’s wrong from the CFO. • Data Infrastructure Expertise: Strong working knowledge of modern data infrastructure – BigQuery, dbt, modern data sourcing tools (Fivetran, AirByte, or similar), and a modern BI layer (Looker, Omni, or similar). • Communication & Influence: Clear written and verbal communication. You can explain a modeling decision to a CS Director, a metric definition to the CFO, and a backfill plan to a data engineer – and each one walks away aligned. • Australia-based: This role is based in Australia. We work in a fully remote setup with strong overlap across our Sydney and Hobart hubs. • What will give you an edge? • High-Growth SaaS Experience: Time spent in a high-growth tech business, especially through the scale-up phase where the data layer has to evolve underneath a moving business. • RevOps Fluency: Hands-on experience working alongside Revenue Operations – territory and quota modeling, pipeline hygiene, forecast inputs, comp data. • Forecasting & Conversational Analytics: Exposure to forecasting workflows or conversational analytics surfaces, and a view on how the modeled layer needs to support them. • Finance Adjacency: Experience building models that bridge from Revenue analytics into FP&A – the seams where ARR meets recognised revenue, where pipeline meets plan. • Lifecycle Across the Stack: Familiarity with adjacent source systems – billing platforms, product usage data, customer success tooling – and how their data needs to slot into a coherent revenue layer. • Marketing Experience: While primarily focused on Revenue, in time there will be opportunities to provide support for the broader organisation, especially our Marketing function.