Job Description:
Lead and scale the Audience engineering team for Big Data & ML at Triton Digital Canada Shape the technical strategy for scalable data and ML platforms to power products and insights Collaborate with product and marketing stakeholders to ensure DMP integration and audience data strategies align with business goals Set the strategic direction for Big Data and ML Engineering; align 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 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 sharedRequirements:
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.Benefits:
