Staff DataOps Engineer (x/f/m)

Your Impact

We are looking for a Staff DataOps Engineer to join the Data and AI 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 feel this job description matches your skill set, we still encourage you to apply.

You'll be a great fit if you:

You have 7+ years of experience after graduation as a Staff Data Platform Engineer, Staff DataOps, Staff Site Reliability Engineer, or in a similar role, with a history of architecting and scaling robust data platforms

You have extensive experience with Google Cloud Platform and a command of Kubernetes & Terraform for automated deployments, and you are an authority on implementing network and IAM security best practices

You have deep technical proficiency in orchestrating data pipelines using Airflow or Dagster, deploying applications to the cloud, and leveraging modern data warehouses such as BigQuery

You are highly skilled in programming with Python, and have a solid understanding of software development principles

You are an excellent troubleshooter who excels at diagnosing and fixing data infrastructure and identifying performance bottlenecks, and a strong communicator who can articulate complex technical concepts to both technical and non-technical audiences

It would be fantastic if you:

Have hands-on experience building and deploying APIs, with a strong preference for frameworks like FastAPI, and are skilled at designing APIs that provide reliable and efficient access to data

Have actively applied data governance principles to manage data quality, security, and compliance, and understand how to implement controls that protect sensitive information

Are experienced with CI/CD tools and methodologies for data-related projects, and can build automated pipelines that streamline development, testing, and deployment

Have practical experience with cloud cost optimization and FinOps principles, actively experimenting with cost-reduction strategies, and are comfortable analyzing infrastructure spending and optimizing resource allocation