About Joko
At Joko, our mission is to we help consumers save time and money when shopping online or in-store. Founded in Paris, Joko is a tech company and certified B Corp with over 105 talents across Paris, Barcelona, and New York (and beyond). More than 6 million users already save money every day at 10,000+ merchants with Joko. Today, Joko is an AI shopping app: with Juno, our shopping assistant, users can find the right product at the best price in only a few seconds.
The Data Team
The Data team at Joko is turning mountains of data into actionable insights for all the teams. Our mission is to empower the company to make informed decisions on solid, trustworthy foundations.
- State-of-the-art analytics & data stack: We build top-notch analyses, predictive models, and robust data infrastructure. We operate a modern data stack (Snowflake, dbt, Airbyte, and Metabase) and continuously raise the bar on scalability, reliability, and performance.
- AI-driven autonomy for stakeholders: We are doubling down on the combination of AI and data to unlock a new level of autonomy for our stakeholders, seamlessly bridging data insights with the AI tools we use.
- Spread the data culture: We work hand-in-hand with our stakeholders, providing support and training on data tools, and building close relationships to ensure our solutions align perfectly with their operational needs.
Responsibilities
As a Data Engineer, you will own and scale our data infrastructure, working closely with Data Analysts, Product Managers, and Engineers to build a reliable, secure, and high-performing data platform.
- Scale our data infrastructure: Lead the evolution of our stack to make it more scalable, reliable, and cost-efficient.
- Power AI initiatives: Lay solid data engineering foundations that enable AI data products.
- Design and maintain data pipelines: Build robust processes to ingest data from multiple sources and orchestrate them efficiently.
- Unlock scalable data modeling: Support Data Analysts by improving dbt project organization, factorizing jobs, and ensuring quality and scalability of transformations.
- Ensure data quality & observability: Implement monitoring, testing, and alerting systems to ensure the freshness, reliability, and accuracy of data.
- Manage data access & governance: Define and enforce access control policies to ensure data is secure, well-permissioned, and compliant.
- Implement documentation & knowledge sharing: Ensure models, pipelines, and workflows are well-documented.
- Tackle exciting challenges ahead: Support new market launches, manage growing data volumes, and help centralize pipelines within an orchestration tool.
What we offer
- Flexible remote: If you live in Paris, you can choose to work from our office or from home. If you live elsewhere, we can provide access to a coworking space and a coworking budget.
- Work from anywhere: You can work from most countries in the world for up to 3 months per year.
- Top-market compensation: €70K – €100.2K.
- Equity: Equity for everyone with the chance to own a piece of what you build.
- AI development: Half-day each week dedicated to leveling up with AI by exploring new tools, iterating hard, and sharpening your skills.
- Team culture: Yearly offsite in amazing locations and budget for team-building events & monthly in-person gatherings.
- Wellness: Contribution to your ClassPass subscription.
- Parental leave: 8-week leave paid 100% for the second parent.
- Full list: Check the full list here.
Requirements
- Experience: 5+ years of experience in data engineering or a similar role, with demonstrated ownership over building and/or scaling data infrastructure.
- Track record: Led the implementation or scaling of a modern data stack (e.g., Airflow, dbt, BigQuery/Snowflake, event streaming, etc.) in a startup or scale-up environment.
- Technical skills: Proficient in SQL and Python. Solid hands-on experience with orchestration tools (Airflow or similar) and cloud environments (Snowflake, GCP, AWS).
- Architectural thinking: Strong understanding of data modeling, warehousing principles, and performance optimization techniques.
- Interest in AI: Genuinely curious about AI and its applications. You use AI in your daily work and you are interested in applications related to the data field.
- Mindset: Pragmatic, curious, and proactive. You value clean architecture, documentation, and continuous improvement.
- Collaboration: Able to clearly communicate with both technical and non-technical stakeholders.
- Languages: Fluent in English, both written and spoken.
