Staff AI Data Engineer: Build Scalable AI Pipelines

Doctolib; Paris; Hybride; EUR 110 000 - 150 000; Plein temps

Avantages offerts par ce poste

Free comprehensive health insurance

Parent Care Program

Mental health and coaching services

Flexible days policy

RTT

Swile lunch voucher

Résumé du poste

Doctolib is seeking a Staff Data Engineer - AI in Paris, hybrid mode, to build end-to-end data pipelines powering AI features for healthcare professionals and patients.

You will design data capture, ingestion, and monitoring systems using Python, Dagster, BigQuery, and DBT, enabling AI model development and robust analytics. Collaborate with cross-functional teams in a cloud-native environment.

Qualifications

• 7+ years of experience as Senior or Staff Data Engineer or similar with 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.
• Experience with Google Cloud Platform (GCP) stack and collaborating with data teams.

Responsabilités

• Design and implement data capture and ingestion systems ensuring data quality and GDPR compliance.
• 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).
• Collaborate with Data Platform teams to optimize infrastructure, scalability and cost management.

Connaissances

Python

SQL

DBT

GCP

Vertex AI

ML platforms

Outils

Dagster

BigQuery

Kafka

Debezium

Metabase

Tableau

Description du poste

Doctolib is seeking a Staff Data Engineer - AI in Paris, hybrid mode, to build end-to-end data pipelines powering AI features for healthcare professionals and patients.

You will design data capture, ingestion, and monitoring systems using Python, Dagster, BigQuery, and DBT, enabling AI model development and robust analytics. Collaborate with cross-functional teams in a cloud-native environment.