Requirements

Proven delivery experience as a data, business intelligence or analytics engineer
Hands-on data modeling and data warehousing skills demonstrated in large-scale data environments
Experience with software development lifecycle in analytics (e.g. version control, testing, CI/CD)
Excellent SQL and data transformation skills, ideally proficient in dbt or similar tools
Familiarity with at least one cloud technology: Snowflake, AWS, Google Cloud, or Microsoft Azure
Passionate about sales, finance, customer, marketing and/or product analytics data
Good attention to detail to identify and resolve data quality issues

What You'll be Doing

Design and implement high-performance, reusable, and scalable data models for the data warehouse using dbt and Snowflake
Design and implement Looker structures (explores, views, etc) enabling self-service analytics across the organization
Collaborate closely with data analysts and business teams to understand requirements and provide data ready for analysis and reporting
Continuously discover, transform, test, deploy, and document data sources and data models
Apply, help define, and champion data warehouse governance: data quality, testing, documentation, coding best practices, and peer reviews
Take initiative to improve and optimise analytics engineering workflows and platforms

Hybrid working model offering flexibility with three days per week in the office to support collaboration and connection
Environment that enables high performers to thrive through real ownership, fewer blockers, and meaningful work
Fast-paced workplace where ambition meets opportunity and individual growth is supported
Inclusive team culture supporting diversity and accessibility to ensure a comfortable working environment