Are you a visionary leader with a passion for data and emerging technologies? Do you thrive in collaborative environments where innovation, team growth, and technical excellence go hand in hand? Join us as we redefine how audio streaming data powers our products and insights.
We are seeking a Director of Big Data & Machine Learning Engineering to lead and scale our “Audience” engineering team. You will shape the technical strategy, drive the execution of scalable data and ML platforms, and empower a team of talented engineers and scientists to push boundaries.

IN THIS LEADERSHIP ROLE, YOU WILL:

• Collaborate with product and marketing stakeholders to ensure DMP integration and audience data strategies support business goals.
• Set the strategic direction for Big Data and ML Engineering, aligning technical goals with business objectives.
• Lead, coach, and develop a high-performing team of developers, data engineers, and MLOps professionals.
• Drive the design and evolution of our data processing and machine learning infrastructure to support massive-scale streaming data.
• Collaborate closely with product, data science, and platform teams to translate advanced analytics and models into robust production-grade systems.
• Establish and promote engineering best practices across architecture, scalability, DevOps, security, and testing.
• Champion a DevOps mindset and a CI/CD culture, ensuring high-velocity, reliable software delivery.
• Oversee the ML lifecycle, including experimentation, model training, deployment, monitoring, and continuous improvement.
• Evaluate and advocate for new technologies that enhance performance, agility, or capability.
• Foster a culture of learning, ownership, and psychological safety, where innovation thrives and knowledge is shared.

YOU’LL THRIVE IN THIS ROLE IF YOU HAVE:

• Solid understanding of Data Management Platforms (DMPs), audience segmentation, and how first-party data can be leveraged for personalization and targeting.
• Proven experience leading engineering teams, preferably in Big Data and/or ML-focused environments.
• Deep technical expertise in Scala and Python, along with Big Data frameworks such as Apache Spark.
• Strong knowledge of distributed systems, real-time data processing, and data modeling at scale.
• Experience with cloud platforms (e.g., AWS), containerization technologies (Docker, Kubernetes, OpenShift), and CI/CD pipelines.
• A solid background in ML Engineering/MLOps, including tools like Airflow, model monitoring, and reproducibility best practices.
• A track record of collaborating cross-functionally and influencing technical and non-technical stakeholders.
• Excellent communication, coaching, and mentoring skills.
• A mindset rooted in Agile values, team empowerment, and continuous improvement.
• 8+ years of experience in data/ML engineering, with at least 3 years in a people management or tech leadership capacity.
• English communication skills are a must. French is an asset.