Data Engineer

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 120 talents across Paris, Barcelona, and New York (and beyond). More than 7 million users already save money every day at 10,000+ merchants with Joko.

From cashback and automatic coupons to price alerts, we've kept expanding our products to make shopping smarter. 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, with recommendations that get sharper the more they use it.

Having reached profitability in our core market, we're now scaling globally, with a strong focus on the US.

It's still day 1, come build the future of shopping with us!

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. This is a high-impact role with significant autonomy as we invest seriously in data engineering.

Your responsibilities will include:

• Scale our data infrastructure: Lead the evolution of our stack to make it more scalable, reliable, and cost-efficient. Anticipate growth in data volume and complexity, and design systems with performance in mind.

• Power AI initiatives: Lay solid data engineering foundations that enable AI data products that are used by all stakeholders across the company.

• Design and maintain data pipelines: Build robust processes to ingest data from multiple sources (internal systems, APIs, external tools) 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 across the stack.

• Ensure data quality & observability: Implement monitoring, testing, and alerting systems to ensure the freshness, reliability, and accuracy of data across the company.

• Manage data access & governance: Define and enforce access control policies (e.g., in Snowflake, Metabase) to ensure data is secure, well-permissioned, and compliant.

• Implement documentation & knowledge sharing: Ensure models, pipelines, and workflows are well-documented to support onboarding, collaboration, and long-term autonomy of the team.

• Tackle exciting challenges ahead: Support new market launches, manage growing data volumes, and help centralize pipelines within an orchestration tool.

• Experience: You have 5+ years of experience in data engineering or a similar role, with demonstrated ownership over building and/or scaling data infrastructure.

• Track record: You have 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: You are 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.