Analytics Engineer

📋 Description

• Build feature marts for ML pipelines with production-ready data models
• Design data transformations using DBT across source systems
• Create datasets enabling self-service analytics across Product, GTM, and Customer Success
• Develop dashboards and reports in QuickSight for stakeholders
• Perform ad-hoc analyses to inform product decisions
• Ensure data quality and reliability via testing, documentation, and monitoring

🎯 Requirements

• Experience: 3-5 years of analytics engineering, data engineering, or similar roles
• Autonomy: Ability to work autonomously in a fast-paced, evolving environment
• Strong communication skills: translate technical concepts for non-technical stakeholders
• Strong SQL skills; write complex queries, optimise performance, and work with large datasets
• Experience with DBT (or similar transformation tools) and data modeling best practices
• Data visualization experience: QuickSight preferred; other BI tools like Tableau/Looker/Power BI are helpful
• Python for data manipulation: pandas, scripting, data wrangling
• AWS data services: Redshift, Athena, S3, or similar

Nice to have

• Experience in e-commerce or SaaS environments
• Familiarity with ML feature engineering and productionization
• Experience with data orchestration tools (Airflow, Dagster, etc.)
• Understanding of data governance and documentation practices
• Experience working in high-growth startup environments

🎁 Benefits

• Work remotely in the AU
• 12 weeks of Paid Family Leave at 100%
• Office stipend setup
• Opportunities for training + development
• Data backed and competitive compensation strategy
• 4 weeks of annual leave