AI Summary
Design, build, and maintain production data pipelines for ingestion, transformation, and orchestration. Model and structure data in a warehouse to support engineering, product, and research teams. Own end-to-end data infrastructure with a focus on reliability, performance, and cost.
Key Highlights
Production data pipelines and warehouse ownership from day one
Full-stack data engineering with SQL, Python, and modern data stack
Real-time data integration from diverse sources including web scraping
Key Responsibilities
Design, build, and maintain production data pipelines for ingestion, transformation, and orchestration
Model and structure data in the warehouse to be clean, documented, and usable across teams
Own data infrastructure including schema design, migrations, performance, and cost
Provide data support to GTM engineers with curated company and account data
Integrate and route diverse data sources into the warehouse from internal events and third-party feeds
Occasionally build data-extraction jobs including web scraping when needed
Improve data quality, observability, and documentation
Diagnose and fix pipeline issues before they become problems
Jump into data and infra tasks to make systems more robust
Technical Skills Required
Benefits & Perks
Paid time off in line with local regulations
Best medical insurance in France
Hardware, tools, and services provided
Subscriptions for AI agents and IDEs
Team off-sites twice a year
Nice to Have
Streaming/eventing (e.g., Kafka)
Versioning datasets and lightweight data pipelines
dbt for data modeling
Modern ETL tools (Fivetran, Airbyte, dlt)
AWS services (Athena, Glue, S3)
GTM/CRM data workflows and enrichment tools
Web-scraping experience
Rust for internal data tooling
Job Description
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.
About Us
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
What you’ll do
- 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.
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- 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.
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- 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.
Interested in relocating to United Kingdom? Check out our comprehensive Relocation Jobs in United Kingdom page with detailed relocation packages and benefits.
- 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
Compensation Range: $60K - $80K
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