Data Engineer

TLDR: This is a broad, full-stack data engineering role. You'll design and run production data pipelines, model data so it's usable across teams, and build the warehouse and tooling that turn raw data into something people can actually work with. You'll be the second data engineer on the team, that means real ownership from day one, a direct line to how the company operates, and no shortage of problems worth solving.

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.

• 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.

1. Intro call with one of our colleagues

2. Complete the take-home exercise

3. Show your best during the technical interview

4. Final call with our CEO and CTO

Please submit your application in English.