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.
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
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
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
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
Enthusiasm for our working environment explained here: https://bit.ly/Convexity_360L
Compensation: Package includes base salary, a variable component and equity 📈
Benefits/Perks: Work From Home stipend, RTT, lunch vouchers, medical insurance, gym subscription, 1 month parental leave for the second parent.
Balance: Flexible hours, full remote work possible anywhere in France 🏠
Diversity, Equity, and Inclusion: We have 6 active ERGs including Mental Health, Environmental/Sustainability, Women, Parents, LGBTQIA2S+, and Ethnic Diversity. Each group has at least one executive team member serving as a member of the group, bringing greater awareness to each group’s activities and providing a quick path to impact 🤝
Corporate Social Responsibility: Review our CSR Charter: 360learning.com/blog/corporate-social-responsibility-charter 🌎🌏🌍
Culture: A framework that will help you make an impact - envision our way of working and our Convexity Culture: https://bit.ly/Convexity360L & find out more about the teams, product and processes https://bit.ly/42H1ggC 🚀👩🏻💻🏆
Build customer support data models, metrics, and dashboards to explain contact drivers, measure automation and self-service outcomes, monitor operational performance, and help teams prioritize evidence-based improvements.
Build and maintain BI dashboards, reports, and reusable SQL data models, translating business requests into accurate visualizations while improving metric consistency, data quality, and reporting performance.
Own and evolve the governed semantic layer behind company-wide dashboards, self-serve analysis, and AI-driven answers, turning ambiguous business questions into reliable, tested metrics and data models.
Design end-to-end data platforms and analytics solutions, from lakehouse architecture and ELT/ETL pipelines to enterprise Power BI models and dashboards, while advising clients and translating business needs into scalable technical.
Build and maintain reliable data pipelines, products, integrations, and internal analytics tools, partnering with data scientists and engineers to strengthen data foundations and support product decisions.
