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Doctolib is seeking a Senior DataOps Engineer to join the Data and AI Platform team. Your mission is to improve and maintain an efficient, reliable, and scalable platform that enables Data Product developers and owners to develop, deploy, and maintain their data products autonomously at scale, with clear interfaces and full observability. You will ensure seamless data flow across the organization and enable data-driven decision-making.
Key Responsibilities:
- Maintain the Data Product Controller to give stakeholders full responsibility for managing their data products in an automated way via CI/CD and infrastructure as code, securely and reliably with full ownership
- Maintain the Data and AI Platform orchestrator (Dagster) to enable Data Product developers to orchestrate their data products in a decentralized way (Data Mesh), with ownership over their release process and job pipelines
- Monitor the data platform for performance and reliability, identify and troubleshoot issues, and implement proactive solutions to ensure availability
- Offer observability components to empower developer teams and data product consumers with insight into costs, data quality, and data lineage
- Monitor platform costs, identify optimization and saving opportunities, and collaborate with data engineers, data scientists, and other stakeholders
- Contribute to continuous improvement of platform architecture, scalability, and developer experience across teams
Doctolib's tech environment leverages a cloud-native platform supporting web and mobile interfaces across multiple languages and healthcare specialties. The tech stack includes Rails, TypeScript, Java, Python, Kotlin, Swift, and React Native. The company ethically leverages AI across products to empower patients and health professionals.
Job Details:
- Permanent, full-time position
- Hybrid work setup (up to 2 remote days per week)
- Paris, France
- Tech stack: GCP (BigQuery, Cloud Storage, Pub/Sub, Cloud Run, IAM, Monitoring), Kubernetes, ArgoCD, Terraform, Crossplane, Dagster, Python, Datadog, Git
- Start date: as soon as possible
Requirements:
- More than 5 years of experience as a DataOps Engineer or in a similar role, with a proven track record of building and maintaining complex data infrastructures
- Strong proficiency in data engineering and infrastructure tools and technologies (Kubernetes, ArgoCD, Crossplane)
- Expertise in programming languages like Python
- Familiarity with cloud infrastructure and services, preferably GCP, and experience with infrastructure-as-code tools such as Terraform
- Excellent problem-solving skills with a focus on identifying and resolving data infrastructure bottlenecks and performance issues
- Fluent in English
Nice-to-Have:
- Knowledge of data governance principles and best practices for data security
- Experience with CI/CD pipelines for data workflows
