Founding Data Lead: Build Trusted Self-Serve Analytics

Skip Loans; Greater Bendigo; On-site; AUD 180,000 - 240,000; Full time

Benefits offered by this job

ESOP

Competitive compensation

Job summary

Skip is building a fast, data-driven home loan platform in Australia. You will own the data stack end-to-end—from ingestion to trusted, business-ready models—and lead the move toward a single source of truth with self-service.

This is the founding data role with scope to grow into a team, reporting to executive stakeholders and collaborating across Growth, Credit, Finance and Treasury. You’ll apply strong analytics engineering discipline, build defensible metrics, and shape the data culture as

Qualifications

• 5+ years across analytics engineering, data analysis or BI
• Own a production data stack with tested, documented models
• Strong business-facing analysis with stakeholder management
• Define trustworthy metric definitions and a data dictionary
• Use AI deliberately with verification and governance

Responsibilities

• Own the data stack end-to-end from ingestion to business-ready models
• Model for trust with proper grain, keys, and version control
• Establish and own metric definitions and data dictionary
• Build core dashboards and reporting used by board, finance and regulators
• Move toward single source of truth with governed self-serve
• Partner with Growth, Credit, Ops, Finance and Treasury to turn questions into decisions
• Use AI to move fast on mechanical work while preserving accuracy

Skills

Analytics engineering

Data analysis

Business-facing analysis

Communication

Tools

Snowflake

dbt

Fivetran

Hex

Git

Job description

Skip is building a fast, data-driven home loan platform in Australia. You will own the data stack end-to-end—from ingestion to trusted, business-ready models—and lead the move toward a single source of truth with self-service.

This is the founding data role with scope to grow into a team, reporting to executive stakeholders and collaborating across Growth, Credit, Finance and Treasury. You’ll apply strong analytics engineering discipline, build defensible metrics, and shape the data culture as