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We are looking for a Tech Lead DataOps to join a large-scale, international program focused on building and scaling the Group’s Enterprise Cloud Data Warehouse. The platform centralizes global data across major business domains (Finance, Customers, Operations, etc.) using modern cloud data architectures and Agile/Scrum methodologies. In this role, you will lead the transversal platform and reliability efforts, driving industrialization, automation, CI/CD pipelines, and overall platform stability in a fully remote, multicultural environment.
Job Responsibility
Technical Leadership & DataOps Governance: Define and evolve technical standards, ensuring the reliability, scalability, and performance of data workflows
Lead industrialization and automation initiatives across development and deployment processes, supporting multiple squads on DataOps best practices
Contribute to technical roadmap definitions, architecture decisions, and continuous ecosystem improvements
Automation & Platform Engineering: Design, maintain, and evolve internal development and deployment tooling around dbt, Airflow, and Snowflake
Develop and optimize internal CLI tools for automated dbt model generation, YAML testing, DAG creation, and deployment automation
Contribute to the integration of AI/LLM capabilities into development and DataOps workflows to reduce manual operations
CI/CD & Deployment Engineering: Design, implement, and maintain secure and automated multi-environment Data CI/CD pipelines
Ensure deployment quality during release cycles, collaborating with project squads and supporting release governance
Orchestration, Reliability & Operations: Supervise, optimize, and design Apache Airflow orchestration workflows and execution DAGs
Implement monitoring, alerting, and observability capabilities to maximize platform stability and operational efficiency
Contribute to incident resolution and root cause analysis
Requirements
Methodology: Strong knowledge and hands-on experience with Data Vault 2.0 methodology applied to enterprise data platforms
Core Tech Stack: Advanced proficiency in Python (focused on data platforms/automation) and SQL query optimization
Data Ecosystem & Orchestration: Solid hands-on experience with dbt and Apache Airflow (including DAG design and workflow optimization)
CI/CD & Cloud Infrastructure: Good knowledge of DevOps practices using Git/GitLab, Jenkins, Docker, Kubernetes, and Snowflake (or equivalent MPP platforms)
Leadership & Soft Skills: Strong transversal technical leadership, an autonomous/proactive mindset, and excellent communication skills to collaborate with multicultural, distributed teams
Languages: Professional proficiency in both English and French is required
Nice to have
Experience with specific data modeling and automation tools like AutomateDV and DBSchema
Practical exposure to modern observability and data platform reliability practices
Experience or strong interest in integrating AI/LLM tooling (such as GitHub Copilot) into DataOps development and deployment workflows