Data Engineer Ajouter aux favoris
- We've raised $11M from top funds, founders, and senior leaders at OpenAI, Anthropic, HuggingFace, Mistral, DeepMind, Datadog, Sentry, and others
- We process over one hundred million API calls every month
- We fine-tune and train our own LLMs so they run faster and cheaper than any open or proprietary model
- Design, build, and maintain production data pipelines - ingestion, transformation, and orchestration - that are reliable enough to be depended on.
- Model and structure data in the warehouse so it's clean, documented, and genuinely useful to engineering, product, and research teams.
- Own data infrastructure alongside the current data engineer: schema design, migrations, performance, and cost.
- Provide data support to GTM engineers - deliver curated, enriched company and account data and the modeling layer that makes it query-ready.
- Integrate and route diverse data sources into the warehouse, from internal product events to third-party enrichment feeds.
- Occasionally build data-extraction jobs, including web scraping, when a source isn't otherwise available - one task among many, not the core of the role.
- Improve data quality, observability, and documentation so the team can move quickly without breaking things.
- Diagnose and fix pipeline issues before they become someone else's problem.
- Jump into data and infra tasks where needed and make things more robust.
- Solid experience as a data engineer building and running production pipelines and data warehouses.
- Strong SQL and Python, and comfort designing data models that other people build on.
- Hands-on experience with a modern data stack: relational databases, a columnar/analytics store, orchestration, and transformation tooling.
- You've worked with PostgreSQL (or similar) and understand how to structure and query data efficiently.
- A production mindset - you care about reliability, migrations, performance, and cost, not just getting a query to return.
- Able to work independently and own problems end-to-end in a fast-moving, early-stage environment.
- You communicate clearly and can work in English.
- Experience with streaming/eventing (e.g., Kafka ).
- Experience versioning datasets and building lightweight data pipelines.
- Experience with dbt for data modeling / analytics engineering, with modern ETL tools (Fivetran, Airbyte, dlt)
- Experience with AWS (Athena, Glue, S3, etc.).
- Familiarity with GTM/CRM data workflows and enrichment tools (Crunchbase, Clay).
- Some web-scraping experience.
- Comfort with a systems language (we use Rust for internal data tooling and SDKs).
- Join early, with a direct hand in the infrastructure that scales us.
- Real ownership and a broad remit across platform, product, and research data.
- A small, senior team that moves fast and ships.
- Paid time off in line with your local regulations, no matter where you work from.
- Work from Paris (hybrid) + relocation package.
- Best medical insurance in France.
- All the hardware, tools, and services you need.
- Covered subscriptions for AI agents and IDEs/
- Team off-sites twice a year: we've recently been to the Alps and to Saint-Tropez.
- Intro call with one of our colleagues
- Complete the take-home exercise
- Show your best during the technical interview
- Final call with our CEO and CTO
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