Senior DataOps Engineer - Data Platform (Hybrid)
Doctolib
Get a reply from this employer
Your resume and cover letter, tailored to exactly what they’re hiring for.
Benefits offered by this job
Job summary
Doctolib in Paris is seeking a Senior DataOps Engineer to join the Data and AI Platform. You will build and maintain a scalable data platform enabling data product developers to deploy and operate their data products autonomously, at scale, with clear interfaces, full observability, and end-to-end ownership.
Your mission includes CI/CD automation, infrastructure-as-code, and collaboration with data engineers, data scientists, and stakeholders to optimize performance, costs, and reliability for
Qualifications
- 5+ years of DataOps Engineer experience or similar role.
- Proficiency with Kubernetes, ArgoCD and Crossplane.
- Proficiency in Python.
- Experience with cloud infrastructure (preferably GCP) and IaC tools e.g., Terraform.
- Excellent problem-solving and data infra optimization skills.
- Fluent in English.
Responsibilities
- Maintain Data Product Controller to automate data product management via CI/CD and IaC.
- Orchestrate data products using the Data & AI Platform (Dagster) with Data Mesh ownership.
- Monitor data platform performance and reliability, troubleshoot issues, implement proactive fixes.
- Provide observability components for costs, data quality, and data lineage insights.
- Monitor platform costs and collaborate with data engineers/scientists to optimize performance.
- Contribute to platform architecture, scalability, and developer experience improvements.
Skills
Tools
Job description
Doctolib in Paris is seeking a Senior DataOps Engineer to join the Data and AI Platform. You will build and maintain a scalable data platform enabling data product developers to deploy and operate their data products autonomously, at scale, with clear interfaces, full observability, and end-to-end ownership.
Your mission includes CI/CD automation, infrastructure-as-code, and collaboration with data engineers, data scientists, and stakeholders to optimize performance, costs, and reliability for
'/%3e%3cpath%20d='M101.744%2012.4726L102.894%2016.1947L99.0021%2013.2201L101.744%2012.4726ZM105.3%208.40937H100.488L99.0026%203.59473L97.5116%208.41047L92.7%208.40385L96.5965%2011.3834L95.1055%2016.1942L99.0021%2013.2196L101.408%2011.3834L105.3%208.40992V8.40937Z'%20fill='white'/%3e%3cdefs%3e%3clinearGradient%20id='paint0_linear_5593_1381'%20x1='90'%20y1='9.44471'%20x2='99'%20y2='9.44471'%20gradientUnits='userSpaceOnUse'%3e%3cstop%20stop-color='%2300AD70'/%3e%3cstop%20offset='0.998594'%20stop-color='%2300B67A'/%3e%3cstop%20offset='1'%20stop-color='%23DCDCE6'/%3e%3c/linearGradient%3e%3c/defs%3e%3c/svg%3e){kind=small}
