Build and maintain feature marts for machine learning pipelines, working closely with our Data Scientist to ensure production-ready data models
Design and implement data transformations using DBT, creating reliable, well-documented data pipelines from multiple source systems
Create and manage datasets that enable self-service analytics across Product, GTM, and Customer Success teams
Develop dashboards and reports in QuickSight for key stakeholders, translating business questions into actionable insights
Perform ad-hoc analyses to support product and business decisions, moving quickly to answer critical questions
Ensure data quality and reliability through testing, documentation, and monitoring
Collaborate across teams to understand data needs and deliver solutions that scale

3-5 years of experience in analytics engineering, data engineering, or similar roles
Ability to work autonomously in a fast-paced, evolving environment
Strong communication skills: you can translate technical concepts for non-technical stakeholders
Strong SQL skills
you're comfortable writing complex queries, optimising performance, and working with large datasets
Experience with DBT (or similar transformation tools)
you understand data modeling best practices and can build maintainable transformation pipelines
Data visualisation experience
QuickSight preferred, but experience with other BI tools (Tableau, Looker, Power BI) is valuable
Python for data manipulation
pandas, basic scripting, data wrangling
Hands-on experience with Redshift, Athena, S3, or similar cloud data platforms

Analytics Engineer

Key skills