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Jobs / Doctolib

Staff AI Data Engineer (x/f/m)

Doctolib·Paris, Paris

In short

  • →Ingeniero de datos especializado en IA que construye pipelines robustos para sistemas de inteligencia artificial.
  • →Trabajas día a día con Python, Dagster, BigQuery y herramientas de monitoreo para apoyar modelos de IA en producción.
  • →Destacado: trabajas en un entorno cloud-native con enfoque ético en IA y cumplimiento estricto de GDPR.
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What they ask for

  • ✓Más de 7 años como ingeniero de datos senior o staff, con experiencia en IA
  • ✓Experiencia comprobada en construcción de pipelines de datos para sistemas de ML/IA en producción
  • ✓Dominio de Python, SQL y DBT para desarrollo de pipelines
  • ✓Conocimiento del ciclo de vida de modelos de ML (entrenamiento, evaluación, despliegue, monitoreo)
  • ✓Experiencia práctica con GCP (Google Cloud Platform)
  • ✓Habilidades sólidas de colaboración con equipos de ciencia de datos e ingeniería

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonSQLDBTDagsterBigQueryGCSKafkaDebeziumMetabaseTableau

Who should you write to at Doctolib?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

We are looking for a Staff Data Engineer - AI to 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 solution s 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 • You have hands-on experience building data pipelines for AI/ML systems in production • You have a good understanding of ML model lifecycle (training, evaluation, deployment, monitoring) • You have a first experience with Google Cloud Platform ( GCP) stack • You have strong collaboration skills and can work effectively with data science and engineering teams Now it would be fantastic if you: • Have experience with Vertex AI, MLflow, or similar ML platforms • Have experience with AI model monitoring and observability tools • Have worked with annotation platforms and labeling workflows • Have experience with Cursor / Claude • Are familiar with GDPR regulations What we offer • Free comprehensive health insurance for you and your children • Parent Care Program: additional leave on top of the legal parental leave</li

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