Data Engineer

• 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.

Nice to have / Big plus

• 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.

White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. At the core of our platform are policies - simple natural-language rules that define what an AI model should and shouldn't do. We automatically test, enforce, and continuously improve these policies at scale. * 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 We're a small, highly focused team. If you want to work deeply on hard problems, see your work ship to production quickly, and influence how AI safety is actually built - you're the one we need.