Staff DataOps Engineer (x/f/m)
Doctolib - Paris, Paris, France
Posted Mar 23, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified
- Family-building benefits
-
- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
- Not verified
- Relocation assistance
- Not verified
- Childcare support
- Not verified
- Learning budget
- Not verified
- Verification
- Not verified
- Salary
- Not verified
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Market context
- Median wage (BLS OEWS)
- $111,944 national median
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Staff DataOps Engineer (x/f/m) Paris, Paris, France Your Impact We are looking for a Staff DataOps Engineer to join the Data and ML Platform team. Your mission will be to shape our data platform strategy and architecture, driving enterprise-scale solutions that accelerate machine learning initiatives, enable engineering excellence, and unlock business insights. You will work in a team at the heart of Doctolib's data-driven transformation, enabling innovation through robust, scalable data infrastructure that empowers engineers, AI teams, and business stakeholders across the organization. Working in the tech team at Doctolib means building innovative products and features to improve the daily lives of care teams and patients. What you'll build Your responsibilities include but are not limited to: - Design and implement enterprise-scale data infrastructure strategies, conducting thorough impact and cost analysis for major technical decisions, and establishing architectural standards across the organization - Build and optimize complex, multi-region data pipelines handling petabyte-scale datasets, ensuring 99.9% reliability and implementing advanced monitoring and alerting systems - Lead cost analysis initiatives, identify optimization opportunities across our data stack, and implement solutions that reduce infrastructure spend while improving performance and reliability - Provide technical guidance to data engineers and cross-functional teams, conduct architecture reviews, and drive adoption of best practices in DataOps, security, and governance - Evaluate emerging technologies, conduct proof-of-concepts for new data tools and platforms, and lead the technical roadmap for data infrastructure modernization What you'll bring Before you read on: if you don't have the exact profile described below, but you
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