Staff AI Data Engineer — Build AI Pipelines (Remote EU/UK)
Staff Data Engineer on Doctolib's AI team, building end-to-end data pipelines (ingestion, warehousing, monitoring) with Python, Dagster, DBT, and BigQuery on GCP to power AI features for healthcare professionals and patients. Requires 7+ years of data engineering experience including production AI/ML pipelines.
- Compensation
- Not disclosed
- Location
- Paris, France
- Work setup
- Not specified
- Seniority
- Staff
- Employment
- Not specified
- Experience
- 7+ years
- Category
- Data engineering
- Posted
Skills
Must have
- At least 7+ years of experience as Senior or Staff Data Engineer, or similar role including AI data
- Proficient in Python, SQL, and DBT for building data pipelines
- Hands-on experience building data pipelines for AI/ML systems in production
- Good understanding of ML model lifecycle (training, evaluation, deployment, monitoring)
- First experience with Google Cloud Platform (GCP) stack
- Strong collaboration skills; can work effectively with data science and engineering teams
Nice to have
- Experience with Vertex AI, MLflow, or similar ML platforms
- Experience with AI model monitoring and observability tools
- Experience with annotation platforms and labeling workflows
- Experience with Cursor / Claude
- Familiarity with GDPR regulations
Full description
We are looking for a Staff Data Engineer - AIto join the AI team at Doctolib.
As a Staff Data Engineer AI, your mission will be to build robust data pipelines - from data capture to monitoring - to power our AI systems and support our ambition to transform healthcare delivery. You will be embedded in the AI teams delivering AI-powered features to healthcare professionals and patients.
Working in the tech team at Doctolib involves building innovative products and features to improve the daily lives of care teams and patients. We work in feature teams in an agile environment, while collaborating with product, design, and business teams.
Your responsibilities include but are not limited to:
- Design and implement data capture and ingestion systems ensuring data quality, privacy compliance (anonymization, consent, retention), and GDPR adherence
- Build, optimize and maintain end to end data pipelines using Python, Dagster, BigQuery, SQL/Jinja, DBT
- Enable AI model development by providing datasets for training, evaluation, and annotation workflows
- Develop custom monitoring solutions including online metrics pipelines and dashboards (Amplitude, Metabase, Tableau) to track AI system performance
Collaborate with the Data Platform teams to optimize infrastructure, ensure scalability, and manage costs effectively
About our tech environment
- Our solutions are built on a single fully cloud-native platform that supports web and mobile app interfaces, multiple languages, and is adapted to the country and healthcare specialty requirements. To address these challenges, we are modularizing our platform run in a distributed architecture through reusable components.
- Our stack is composed of Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native.
- We leverage AI ethically across our products to empower patients and health professionals. Discover our AI vision here and learn about our first AI hackathon here!
- Our data stack includes: Kafka/Debezium for data ingestion, Dagster/DBT for orchestration, GCS/BigQuery for data warehousing, and Metabase/Tableau for BI and reporting.
Who you are
Before you read on — if you don't have the exact profile described below, but you feel this job description matches your skill set, we still encourage you to apply.
- You have at least 7 years+ of experience as Senior or Staff Data Engineer, or a similar role including AI data.
- You are proficient in Python, SQL, and DBT for building data pipelines