Analytics Engineer

The Data team builds and evolves the data platform that powers critical product features and helps every team make smarter, faster decisions. Our data ecosystem supports hundreds of pipelines, dashboards, and tools, providing the foundation for both day-to-day operations and strategic decision-making. What makes our team unique is our central role across the company: we sit at the intersection of Product, Operations, Customer Success, Sales, and Engineering. As our first Analytics Engineer , you’ll bridge the gap between our data platform and business teams by building trusted datasets, meaningful KPIs, and self-service analytics capabilities. You’ll work closely with our Senior Data Analyst and Data Engineers to improve data models and documentation, strengthen the reliability and efficiency of our warehouse, and help teams become increasingly autonomous with Snowflake, Looker/Metabase, and AI-powered analytics . You’ll then contribute to our broader mission of making data more accessible and actionable across 360Learning. Within 1 month, you will: Discover 360Learning, its platform, teams, and culture Get familiar with our data stack (Snowflake, Looker, dbt, etc.) and our ways of working Understand our data models, ways of working, and self-service analytics strategy Within 3 months, you will: Build reliable, well-documented datasets and KPIs that help teams answer their own business questions Enable teams to access and leverage data through Snowflake MCP, empowering them to answer business questions more independently Collaborate with our Senior Data Analyst to improve documentation, data models, and best practices to strengthen self-service adoption Within 6 months, you will: Partner with Data Engineering to improve warehouse performance, reliability, and cost efficiency Help teams become more autonomous on Snowflake and BI tools by guiding them toward the right datasets and sources of truth Become a go-to partner for teams looking to monitor key metrics, explore data, and make data-driven decisions The Skill Set: Strong SQL skills with the ability to write complex queries and work confidently with data. Hands-on experience with BI and analytics tools, such as Looker, Metabase, or Omni. Experience with modern data warehouses, such as BigQuery, Redshift, or Snowflake. Good working knowledge of Git and version control best practices. Experience with dbt is a strong advantage. Strong interest in AI and emerging analytics tools, with a focus on their practical application to business and data-related challenges. Solid understanding of data modeling and data warehousing principles, with an interest in building reliable, scalable, and efficient data solutions. Curiosity and problem-solving mindset: able to break down ambiguous questions into clear, actionable steps Comfortable collaborating with non-technical stakeholders, understanding their needs, and communicating technical concepts in a simple way. Fluent English (US/UK) / French fluent Enthusi