Director of Development - Big Data & Machine Learning en Triton Digital
Triton Digital · Montreal, Canadá · Hybrid
- Senior
- Oficina en Montreal
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.