About the Role
As our Lead Data Engineer, your mission is to architect, scale, and maintain the backbone of our data ecosystem. You will transform massive volumes of raw signals into actionable intelligence, ensuring our infrastructure is as agile as our growth strategy. You will bridge the gap between high-level data strategy and hands-on technical excellence.
Responsibilities
•Lead the design, implementation, and optimization of distributed data architectures to support massive Batch & Streaming pipelines.
•Ensure the scalability, security, and performance of the infrastructure, maintaining high system availability (99.9%+) for analytics platforms.
•Optimize storage solutions to balance high-speed processing with cost-efficiency.
•Collaborate with software engineers and data scientists to seamlessly integrate AI-driven models into production data workflows.
•Lead and mentor a team of 2 data engineers, fostering a culture of continuous improvement, growth, and technical excellence.
•Set high standards for code quality, documentation, and rigorous peer reviews.
•Oversee project execution, delegate responsibilities, and act as the technical point of escalation for complex data-related roadblocks.
•Guide technical decisions and promote industry best practices in data engineering (CI/CD, DataOps).
•Work closely with product managers, developers, and analytics teams to define data needs and ensure alignment with business objectives.
•Implement robust monitoring, alerting, and automated testing (Data Quality) to ensure the integrity of the data team's output.
•Ensure data security and GDPR compliance across all international jurisdictions and workflows.
•Identify opportunities to leverage new technologies or improve existing workflows to optimize data processing.
•Maintain a deep understanding of data trends and possess the ability to simplify complex problems into executable tasks.
•Encourage and champion the use of Generative AI tools across the team to accelerate development cycles, automate repetitive tasks, and enhance data exploration capabilities.
Requirements
•6+ years in Data Engineering, with at least 2 years in a leadership or "referent" role within fast-paced environments.
•Expert proficiency in distributed data systems, clustering, advanced table types, and materialized views.
•Skilled in designing table sorting keys and fine-tuning database performance.
•Solid programming skills in Python, Golang, and Scala/Java, with deep expertise in Kafka for streaming/batch data pipelines.
•Hands-on experience with on-premise infrastructure (own datacenter) managed by Kubernetes, and familiarity with monitoring stacks such as Prometheus.
•Strong knowledge of column-oriented databases designed for high-volume data processing, vector databases (e.g. Qdrant), and SQL/NoSQL technologies.
•Comfortable working with project tracking tools (Flyspray) and applying CI/CD & DataOps best practices.
•You want to make an impact and move things forward collectively.
•You solve problems pragmatically and analytically.
•You're looking for a fast-moving environment where your agility will be an asset.
•The 80-20 (Pareto) principle holds no secrets for you.
•Your ability to listen encourages you to challenge and improve yourself on an ongoing basis.
Nice to Have
•Interest or hands-on experience leveraging Generative AI tools in daily engineering workflows to boost productivity and innovation.
Conditions
•Flexible work environment adapting to your lifestyle — work from home or from urban offices in Paris, Lille, or London.
•Part of a dynamic and united team, where collaboration, innovation, and mutual support drive collective success.
•Regular social gatherings and company events that foster community and celebrate milestones.
•Working with a company in rapid expansion mode, impacting the advertising technology landscape across Europe and beyond.
•Robust career development support, including training programs, career check-ins with HR, opportunities for internal mobility, and performance feedback sessions conducted quarterly or semi-annually, depending on role.
•Work-life balance support with additional rest days (RTT), provided based on position and tenure.
•Robust health benefits plan, covering you and your family.
•Swile card for meals.
