SafetyCulture

Technology

FinanceAnalyticsEngineer

A$135–185k ~AI est. Sydney, New South Wales, Australia FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“Finance Analytics Engineer at SafetyCulture. Skills: Finance data domain, dbt models, Semantic layer. Build Finance semantic layer. Own Finance semantic layer”

Industry & Context.

Technology
Problems you'll solve

Finding answers; Navigating ambiguity

What They're Looking For.

Must Have

5+ years Finance collaboration, dbt skills required

Nice to Have

Experience with Finance team, Experience with Accounting team, Experience with Finance Systems team, NetSuite familiarity, Workday familiarity, Zuora familiarity, HiBob familiarity, ERP platforms familiarity, Payroll platforms familiarity, Billing platforms familiarity, Financial close processes exposure, Revenue recognition exposure, Period-end reporting cycles exposure, Owning dbt stack slice, Building AI-ready semantic layers, High-growth SaaS environment background

What You'll Do.

Build Finance semantic layer

Own Finance semantic layer

Apply software engineering best practices

Ensure model descriptions

Ensure column definitions

Ensure metric ownership

Version intentionally

Use SQL for data loading

Use Python for data loading

Use Macro for data loading

Use SQL for transformation

Use Python for transformation

Use Macro for transformation

Understand business rules

Encode business rules

Translate Finance requirements

Validate outputs against benchmarks

Design access control

Implement access control

Define permission tiers

Manage service accounts

Partner with Engineering

Implement data quality checks

Maintain documentation

Partner with Data Engineering

Manage data infrastructure

Optimize data infrastructure

Consume shared dimension tables

Make semantic layer queryable

Make semantic layer reliable

How You'll Work.

Team & Collaboration

Finance stakeholders; Analytics Engineering teams; Data Engineering teams; IT; Engineering

Communication Scope

Translate business requirements

Process & Methodology

Version control, CI/CD deployment

Full Job Description

## Description Why join us? We’re a global tech company,  just not the kind you’re picturing. Sure, we’ve got catered lunches, team events, cool merch, and yes... dogs in the office. But that’s not why people join. Our team of nearly a thousand people wakes up every day to make our product and our customers’ lives better. At SafetyCulture, you’ll hear “yes, let’s give it a shot” more often than “that’s not how we do things here.” People join because we’re building tools that make work better for the 3 billion people who keep the world moving - factory floor operators, baggage handlers, truck drivers, servers, store assistants. The ones who make things happen. We’ve got the scale and innovation you’d expect from big tech. The difference? No endless layers of sign-off. No corporate theatre. Just smart, experienced people solving real problems fast . The scale is big. But the ownership’s personal. Every full-time team member gets equity - real skin in the game. When we grow, you do too. We’re not perfect, no company is. But this next chapter of our growth is about scaling with intelligence, not just size - fueled by operational maturity, a clear vision, and a strong focus on AI.  This is big tech impact, without the big tech ick. If that excites you more than it scares you, you’ll fit right in. The Role SafetyCulture's Finance function is building an AI-powered operating model, automating the mechanical, repeatable work across FP&A, Treasury, Accounting, Tax, AR, AP, Legal operations, and beyond so the team can focus on judgement, analysis, and the decisions that move the business. We're looking for a Finance Analytics Engineer to own the data foundation that makes this possible. Where our Data Engineering team ensures data flows reliably into Redshift, you turn those raw sources into a trustworthy, governed, AI-ready Finance semantic layer that Finance workflows and AI agents can build on. That means owning the dbt transformation layer for all Finance source systems,

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