Founding Data Lead

Skip Loans; Bunbury; On-site; AUD 180,000 - 270,000; Full time

Benefits offered by this job

Competitive compensation

ESOP/Equity

Job summary

Skip is seeking a founding data engineer to own the data stack end-to-end in Australia. You’ll build ingestion pipelines to Snowflake, shape the model layer, and deliver trusted, self-serve data for dashboards, exec packs and regulator reporting.

This is a true founding role with ownership to define standards and scale a data function. You’ll collaborate with Growth, Credit, Ops, Finance and Treasury, use AI thoughtfully, and have a path to lead a team.

Qualifications

• Senior capability with autonomy and breadth; able to own outcomes end-to-end.
• Production data stack ownership from ingestion to validated models.
• Strong business-facing analysis and stakeholder management.
• Experience using AI deliberately with verifications.

Responsibilities

• Own the data stack end-to-end from ingesting raw data to clean, reconciled models.
• Model for trust with proper grain, keys, structure and tested versioning.
• Establish metric definitions and a data dictionary for consistency.
• Build core dashboards and regulator-facing reporting with defensible numbers.
• Move toward a single source of truth and scalable self-service.
• Partner with Growth, Credit, Ops, Finance and Treasury to drive decisions.
• Use AI to accelerate mechanical work while preserving accuracy.

Skills

Analytics Eng

Data modeling

dbt

Snowflake

Fivetran

Stakeholder comms

AI experimentation

Tools

Hex

Git

SQL

Job description

Job Description

Mission

Skip is building the fastest, most intelligent home loan platform in Australia - and we increasingly run on data: credit performance, acquisition economics, settlements and servicing, and the numbers our board, warehouse funders and regulators rely on. This is our first dedicated data hire . The job is to turn raw, ingested data from a wide array of sources into trusted, decision-ready answers - and to build the modelling discipline so those numbers stay trustworthy as we scale many times over.

About the role

We’re hiring the person who, faced with a new business question, instinctively asks: how do we model this once, test it, and make it self-serve? - and then builds the clean, tested data models and shared definitions that make the answer obvious to everyone - whether querying and interpreting from a dashboard or from an agent chat. A founding generalist who is genuinely disciplined at modelling and a strong, business-literate communicator and the founding owner of a function we expect to grow - you may build and lead the data team that follows.

You will own three parts that most companies split across two or three people:

• The ingestion layer - the pipelines that land raw data from our source systems into Snowflake reliably and on time, so everything downstream is built on complete, fresh data.

• The model layer - the transformation, dimensional modelling, testing and documentation that turn raw Snowflake data into clean, reconciled, business-ready tables (dbt-style: staging → intermediate → marts).

• The analysis - partnering with all teams and Execs to answer the questions that actually move the business, and turning the numbers into decisions.

The thread connecting them is the same: make the trusted number the easy number. You measure your success not by how many dashboards are shipped, but by how many decisions get made confidently on numbers people trust.

The opportunity

We are a small, high-talent-density team scaling our business with technology. The companies that win this phase keep their teams small and their leverage high. Data is usually where that breaks: trust erodes, every team defines metrics differently, and answering a simple question turns into a week of reconciliation. The opportunity here is to prove the opposite - that one excellent person, building the right models and definitions early, can give the whole business trusted, self-serve answers while the team stays lean.

Key Responsibilities

• Own the data stack end to end - from ingesting raw source data into Snowflake through to the clean, reconciled, business-ready models the whole company relies on (the loan book, arrears, originations and the acquisition funnel).

• Model for trust: the right grain, keys and structure so marts are business-ready and reconcile across all reporting levels — with testing and version control as the default, not an afterthought.

• Establish and own metric definitions and a data dictionary - so numbers mean the same thing in credit, finance and the board pack.

• Build the core dashboards and reporting the business runs on - high-signal views people actually use - and own board, warehouse-facility and regulator-facing reporting so the numbers we report externally are trustworthy and defensible.

• Build toward a single source of truth and governed self-service, so the data function scales without becoming a bottleneck as request volume grows.

• Partner with Growth, Credit, Ops, Finance and Treasury - clarifying vague questions and ending with a concrete recommendation, not just a chart, and pushing back when a request is wrong.

• Use AI and technology to move fast on the mechanical work while owning the judgement and verification that keeps the numbers honest.

What you will bring

We’re looking for senior capability, expressed as autonomy and breadth more than years — but as a guide, this typically looks like 5+ years across analytics engineering, data analysis or BI, with the seniority to own outcomes end-to-end and set standards from scratch.

• You have owned a production data stack - the pipelines feeding the warehouse and a tested, documented, version-controlled model layer on top - not just “used dbt” once.

• Strong, demonstrable business-facing analysis - you have good instincts about which insights matter, can manage stakeholders and metric definitions, and reliably turn numbers into decisions.

• You think in definitions and trust - your instinct on seeing inconsistent numbers is to model and define them once, not to patch another query.

• You use AI deliberately and verify it - you wield agents to move fast on the mechanical work and own the verification that keeps outputs honest.

• You communicate trade-offs clearly , make pragmatic calls about what is fit-for-stage versus over-engineered, and are happy being the founding owner who sets the standard others build on.

Our stack today (a starting point - you’ll shape where it goes): Fivetran for ingestion, Snowflake as the warehouse, and Hex for reporting.

On requirements: we care far more about skills, approach and the ability to learn than about specific certifications or a particular industry background. If you have strong modelling discipline and genuine business instinct, we want to hear from you - even if your résumé doesn’t tick every box above. But we won’t relax on git and testing fundamentals.

Why Join us

• Build the data function, don't maintain one. This is the first dedicated data hire - you're not inheriting a tangle of broken pipelines and conflicting metrics, you're defining how Skip models, defines and trusts its numbers from scratch. Real founding ownership, not a delegated slice.

• Own the numbers the whole company runs on. From ingestion through to the board pack, warehouse-funder and regulator reporting - you sit at the centre of credit, growth, finance and exec, turning vague questions into decisions. Few roles give one person this much leverage over how a business actually thinks.

• A path to build and lead a team. We're hiring one excellent founding owner today - but as request volume and the business scale, the opportunity to grow this into a data team you lead, or to deepen as the principal who sets the standard, will be explicitly on the table.

• Competitive comp and ESOP. We pay competitively and back it with equity that reflects the founding nature of this role. As Skip scales many times over, you share in the upside you help build.

• Work at the frontier of data and AI. Full support from an internal product and engineering team, a modern stack you'll shape (Fivetran, Snowflake, Hex), and a mandate to wield AI on the mechanical work while you own the judgement that keeps numbers honest. This is analytics engineering for the modern era, not hand‑built spreadsheets and reconciliation weeks.

• Serious company, serious scale, real impact. Backed by leading US venture funds and global credit partners Skip is in a true hyper‑growth phase - loan book scaling rapidly, major distribution partnerships live. Your work helps hard‑working Australians Skip to home ownership sooner, on a team that moves fast and backs each other to do the best work of our careers.