Analytics engineer (f/h)

Foodles, c’est la cantine en mieux : plus simple, plus généreuse, et plus conviviale ! Nous ré-enchantons la vie au bureau en proposant une solution de restauration sur-mesure, livrée clé en main, afin que chaque collaborateur puisse accéder à une alimentation variée et équilibrée et à moindre coût.

L’expérience convive et le respect de l’environnement sont au cœur de notre concept, alliant des frigos connectés accessibles en libre-service toute la journée et un service de commandes du jour. Nous respectons une charte qualité stricte (produits frais, pêches issues de filières responsables, etc.) afin de garantir une offre responsable.

Au-delà de notre offre, nous avons à cœur de placer ces engagements environnementaux et humains au cœur de notre vie d’équipe. Nous avons envie de faire bien, mais surtout de faire mieux… et surtout que notre générosité ne s’arrête pas à nos plats :)

Eco-responsabilité : au-delà de nos produits, nous nous impliquons pour adopter des gestes éco-responsables afin de minimiser l’impact de nos activités.
Partage & entraide : nous donnons nos invendus à des associations locales qui les distribuent à des personnes dans le besoin, et nous proposons également à nos collaborateurs de s'investir dans la vie associative avec le Secours Populaire.
Bien d'autres initiatives se développent encore et nous comptons sur nos futures recrues pour y participer !

Descriptif du poste

Foodles is revolutionizing the workplace canteen experience simpler, more generous, and more convivial! Using our proprietary connected fridge technology, we provide fresh, seasonal meals at affordable prices. Our system automatically detects the dishes taken from the fridges and charges guests accordingly. As a leader in our market in Europe, we serve nearly a thousand clients across France and have expanded into the United Kingdom.

Your Mission

As part of the Data Platform team, your mission will be to ensure the accessibility, understanding, and quality of data at Foodles, serving both analytical (BI) and applicative (Data Science) needs. You will also contribute to the setup and maintenance of tools that leverage this data, from optimizing dispatch decisions for our fridges in coordination with the Supply & Data Science team to managing our Data Warehouse and BI tools.

To achieve this mission, your team undertakes the following key activities:

1. Build and maintain the data platform: Ensure a robust infrastructure for efficient data management and accessibility.
2. Provide clean, analysis-ready data: Deliver refined and accurate data to support decision-making and algorithm development.
3. Develop and maintain algorithm-supporting code: Implement and sustain a reliable, scalable, and maintainable codebase for production environments.
4. Manage data job orchestration: Optimize and streamline the execution of data processes for improved workflow efficiency.

As an Analytics Engineer, you will be primarily focused on the last mission. Your role will be to ensure that data from internal and external sources is accurately fetched, well-structured, and accessible for analysis across Foodles. Your responsibilities will include defining and modeling data in collaboration with business and tech teams, establishing data organization standards, and ensuring overall data quality and comprehension.

Your Future Work Environment

You will be part of a dynamic team composed of:

5. 1 Tech Lead
6. 2 Software Engineers
7. 2 Analytics Engineers (including you!)

Tools You’ll Use Daily:

8. DBT: Your main tool for daily tasks.
9. Data Stack: Dagster, Fivetran, Snowflake.
10. Collaboration & Monitoring Tools: GitHub, CircleCI, Linear, Codecov, Datadog (logs & APM).
11. Infrastructure as Code (IaC): Pulumi (Python-based).

For a more detailed view of our tech stack, check out our tech stack presentation.

Our team structure evolves regularly to align with our diverse responsibilities and the unique challenges of working with data. We currently operate in 6-week development cycles, followed by a 2-week cooldown period dedicated to internal improvements and optimizations.

Your Responsibilities

12. Ensure the correctness and robustness of data by implementing necessary tools.
13. Understand business processes, document data flows, and challenge data quality.
14. Maintain and optimize existing models and pipelines.
15. Write and review high-quality, well-tested code.
16. Propose and implement new best practices and processes to improve the team's efficiency and collaboration.

Ideal Candidate Profile

You are the Analytics Engineer we need if you:

17. Have strong SQL and data modeling skills with knowledge of modern best practices.
18. Are autonomous and can effectively organize your workload.
19. Manage projects with clear communication and take full ownership from design to deployment.
20. Are not only tech-savvy but also interested in understanding business challenges and data applications.
21. Write clear, structured documentation and contribute to improving data model documentation.
22. Are curious, eager to learn, and unafraid to step out of your comfort zone.
23. Prioritize writing simple, well-tested, and maintainable code.
24. Are open to giving and receiving constructive feedback within the team.
25. Are comfortable working in a primarily remote environment.

Bonus Points:

26. Experience in the food or logistics sector.

Recruitment Process

27. 30 min with Dorine our Talent Acquisition Lead.
28. Async tech test (~1h).
29. 30 min of meeting with Jocelyn (N+1)
30. A case study with Jocelyn and 2 peers (François and Charlène)
31. 30 min Call with Lucas
32. Reference check & Lunch at Foodles HQ.

Join us in redefining workplace dining with cutting-edge technology and data-driven solutions! 🚀

At equal qualifications, Foodles prioritizes people with disabilities and other beneficiaries of the employment obligation.

Why join our adventure?

33. A dynamic and highly motivated team where you'll gain autonomy and responsibilities
34. Incredibly affordable meals (really… incredibly) every lunchtime
35. Well-located and easily accessible offices
36. And many more perks! ;)