CFM is seeking a dynamic and experienced Head of Data Platform to lead the development, management, and optimization of our hybrid data platform, encompassing shared services and components (e.g. Data Catalog), CFM’s cloud-based data lake and on-premises infrastructure.

The ideal candidate will have a strong background in data architecture, data engineering, and big data, with a deep understanding of managing large-scale, high-performance, developer-friendly data environments to support cutting-edge data science.

• Oversee the development and maintenance of a secure, scalable, and high-performance data platform and infrastructure that supports advanced data use cases and analytics.
• Work closely with Data Engineering, Data Science and Quant teams to understand their needs and ensure seamless integration of data pipelines and processes into the platform, from development to production.
• Supervise the evolutions of shared components and services used by Data and Quant teams.
• Foster a product-centric approach, using feedback loops to continuously improve the expected features, usability, and performance, ensuring the platform is a value-add to internal users.
• Optimize developer workflows and processes through automation and reusable templates, reducing the time to production.
• Manage a cross-functional team of DevOps, Site Reliability and Software engineers working on the data platform.
• Propose, implement and monitor Key Performance Indicators, in relation to UX and Business added value.
• Collaborate efficiently with Core Technology and Security teams to smoothly integrate into CFM technological ecosystem, stack and standards.
• Serve as the subject matter expert, providing guidance on emerging technologies and potential improvements.
• Ensure globally the efficiency and relevance of the data platform to CFM business needs, define and pilot the related roadmap.

• Bachelor’s or master’s degree in computer science, Data Engineering, or related field.
• Minimum of 10 years of experience in data engineering or data architecture, with at least 5 years in a leadership role.
• Proven track record of managing hybrid data environments in challenging contexts, driving the adoption of cloud technologies and designing platforms with a developer-first, self-service mindset.
• Expertise in data architecture, including data lakes, ETL/ELT pipelines, distributed computing (e.g., Spark), and database technologies (SQL, NoSQL).
• Strong knowledge of cloud technologies (AWS S3, Athena, EMR, Google BigQuery, Azure Data Lake, …) and containerization (Docker, Kubernetes).
• Proficient in programming languages, including Python, and software craftmanship (code quality, test-driven development, continuous integration, change and release management, …).
• Proven achievements with Platform Engineering tools and methodologies, including CI/CD pipelines, Infrastructure-as-Code (Terraform, CloudFormation), and self-service capabilities.
• Excellent leadership, team management and project management skills, applicable to cross-functional contexts.
• Ability to solve complex problems and make strategic decisions.
• Excellent communication skills, with the faculty to translate technical concepts into business outcomes for non-technical stakeholders.
• Capacity to work in a fast-paced, high-stakes environment, with a commitment to professional development and continuous learning.
• Knowledge of financial markets, governance and regulatory requirements and/or quantitative research is a plus.