Analytics Engineer

This is a fully remote position, open to applicants in Australia.

📋 Description

• Ownership of Revenue Data Layer: Create, develop, and sustain the core revenue data models in dbt, including ARR, pipeline, bookings, churn, expansion, retention, attach rates, and connect them with customer, opportunity, and product contexts. This domain is entirely yours.

• Collaboration with Stakeholders: Forge strong, lasting relationships with leaders and operators in Sales, Customer Success, and Revenue Operations. Convert vague, evolving requirements into well-defined models and clear metric definitions that stakeholders can trust and utilize effectively.

• Gathering Requirements: Engage with the users of the data to understand the operational realities behind their requests prior to writing any SQL. Differentiate between the actual decision being made and the requested artefact, and return with a more refined proposal than what you received.

• Pragmatic Delivery: Excel at the 80/20 principle. Deliver the version that facilitates decision-making this week while also constructing the foundational elements that support the next quarter. Know when a quick dbt model with a clear caveat is appropriate, and when a comprehensive, governed, tier-one data product is necessary. Make these judgments explicit rather than implicit.

• Crafting Models: Create dbt models that are thoroughly tested, well-documented, efficient, and easy to understand for the next engineer who will work on them. Establish and maintain standards for naming, layering (staging → intermediate → marts), testing, and documentation across the revenue domain.

• Data Products & Tiering: Develop models suited to the specific use case—ranging from exploratory sandbox models for analyst-driven discovery to self-service modeled marts, and up to the regulated, accuracy-critical models that serve Finance, board reporting, and the executive team. Be decisive about what belongs in each tier.

• Commercial Insight: Possess a strong intuition for how B2B SaaS revenue operates—understanding the connections between bookings, billings, ARR, recognized revenue, pipeline coverage, conversion, sales cycle, and retention—and allow that intuition to inform the models you create instead of merely validating them post-facto.

• Detail-Oriented: Revenue figures undergo scrutiny. Reconcile with source-of-truth systems, document edge cases, highlight assumptions, and ensure the number presented in the board deck matches the dashboard. Pay attention to the details, as the executive team will.

• Collaborate with Data Engineering: Partner closely with the data engineering team to manage what is integrated into the warehouse from CRM, billing, product, and finance systems. Be a clear, specific, and respectful client of sourcing—acting as a partner that simplifies the upstream team's responsibilities rather than complicating them.

⛳️ Requirements

• Proven Expertise: Over 5 years of experience in building and managing analytics engineering or modeling work, with a significant focus on Revenue, Sales, or Customer Success within a B2B SaaS environment.

• Revenue Domain Knowledge: Deep understanding of B2B SaaS revenue schemas—ARR, bookings, pipeline, opportunity lifecycle, churn, expansion, contraction, NRR, GRR—and the practical complexities of how these metrics are computed and reconciled in a real business context.

• CRM Proficiency: Strong, hands-on experience in modeling data from HubSpot and/or Salesforce. You are adept at navigating object relationships, history tables, and the discrepancies between CRM data and actual reality.

• Skill in Requirements Translation: Proven ability to convert loose, ambiguous, or evolving requirements into well-structured dbt models, clear metric definitions, and actionable outputs for stakeholders without the need for follow-up questions.

• 80/20 Judgement and Commitment to Proper Building: Capable of delivering a sharp answer swiftly when time is of the essence, while also being able to create a durable, governed data product when necessary. You know which approach to take and why, and can justify your decisions.

• Commercial Insight: Strong commercial instincts—you comprehend why a metric is significant to the business before constructing it, ensuring that your models reflect commercial realities rather than mere schema convenience.

• Meticulous Attention to Detail: Truly thorough. You reconcile, test, document, and scrutinize edge cases. You do not deliver a revenue model only to discover it was incorrect from the CFO’s perspective.

• Data Infrastructure Knowledge: Strong familiarity with modern data infrastructure—BigQuery, dbt, contemporary data sourcing tools (Fivetran, AirByte, or similar), and a modern BI layer (Looker, Omni, or similar).

• Communication & Influence: Proficient in both written and verbal communication. You can clearly articulate a modeling decision to a CS Director, explain a metric definition to the CFO, and present a backfill plan to a data engineer—ensuring each individual leaves the conversation aligned.

• Based in Australia: This position is located in Australia. We operate in a fully remote setup with robust collaboration across our Sydney and Hobart hubs.

🏝️ Benefits

• Monthly Lifestyle Subsidy: Use this benefit to support your financial, physical, and mental well-being.

• WFH Setup Allowance: To ensure you have the optimal working environment, we will assist with your setup within your first three months at UpGuard.

• $1500 USD Annual Learning & Development Allowance: To foster your career growth, all team members can expense development opportunities against this allowance.

• Annual Leave: Paid time off plus two additional UpGuardian leave days to help you recharge.

• 18 Weeks Paid Parental Leave: Available to all parents, regardless of their role.

• Personal Leave Allowance: This includes sick and carer’s leave.

• Fully Remote Working Environment: Although we have offices in Sydney and Hobart, attendance is not mandatory.

• High-Quality Hardware: All team members will receive top-spec laptops suited for their roles.

• Generative AI Subsidy: UpGuard provides paid subscriptions for all team members to access generative AI tools that support their work.