Data Engineer Ajouter aux favoris
- 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: At Joko, we have a strong engineering and tech culture across all teams. 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 and evolve with them over time.
- 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.
- Flexible remote : If you live in Paris, you can choose to work from our office or from home with no constraints. If you live elsewhere, we can provide access to a coworking space and a coworking budget.
- Work from anywhere : Want to spend a month in Italy while working? You can work from most countries in the world for up to 3 months per year.
- Top-market compensation
- Equity for everyone with the chance to own a piece of what you build
- Half-day each week dedicated to leveling up with AI by exploring new tools, iterating hard, and sharpening your skills
- Yearly offsite in amazing locations and budget for team-building events & monthly in-person gatherings
- Contribution to your ClassPass subscription
- 8-week leave paid 100% for the second parent
- ...and much more, check the full list here !
- Intro call: Quick screening with the Hiring Manager or the Talent team.
- Step 1 - Team interview (45 min): Conversation with two Joko team members (could include the Hiring Manager, people from the team you'd join, or colleagues from other teams).
- Step 2 - Role-specific assessments
- For non-engineering roles : A take-home case study followed by a 45-min interview. We assess both your output and how you think in real time. The exercise will be relevant to your role (e.g. analysis, strategy, or process design).
- For engineering roles : A 90-min live technical interview on CoderPad covering code understanding, review, system design, and product thinking (with AI serving as a collaboration tool).
- Step 3 - Leadership interview (45 min): Conversation with a SteerCo member and a Founder.
- References: Up to 3 calls with former colleagues or managers.
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