About the role

MLOps Data Engineer bridging data science and production systems at Triton Digital. Designing CI/CD pipelines and optimizing data processing with Apache Spark for advertising systems.

Responsibilities

Design, implement, and maintain CI/CD pipelines for machine learning workflows using tools like GitHub Actions, Azure DevOps, or Jenkins.
Build and optimize data processing pipelines in Apache Spark (PySpark and Scala) for large-scale, distributed listener datasets.
Deploy and manage Databricks environments, ensuring efficient cluster usage, job scheduling, and cost optimization.
Collaborate with data scientists to productionize ML models, integrating them into scalable APIs or batch processing systems that feed real-time, machine-readable audience signals.
Implement automated testing, monitoring, and alerting for ML pipelines to ensure the reliability and reproducibility that certified buyers require.
Champion best practices in version control, model registry management, and environment reproducibility.
Help evolve our listener data infrastructure toward agent-compatible supply — live, structured, queryable data feeds that autonomous buying systems can discover and act on without human mediation.

Proven experience in Data Engineering, MLOps, and DevOps roles with a focus on automation and scalability.
Strong programming skills in Python, with hands-on experience in Apache Spark.
Scala is a huge plus.
Advanced expertise in Databricks, including Delta Lake, structured streaming, feature engineering.
Solid understanding of CI/CD principles and tools (e.g., GitHub Actions, Jenkins, Azure DevOps, GitLab CI, ArgoCD).
Familiarity with cloud platforms (AWS, Azure, or GCP) for data and ML workloads.
A problem-solving mindset and the ability to work closely with cross-functional teams.
Strong architectural mindset, capable of evaluating trade-offs across cost, performance, scalability, and maintainability when selecting tools and designing systems.
Experience working with containerized and orchestrated environments (Kubernetes / OpenShift), including deployment, scaling, and fault tolerance of data and ML workloads.
Advanced English required.
French is an asset.
Familiarity with IAB data standards, programmatic advertising infrastructure, or AdTech data pipelines is a strong asset.

Fully remote position (must be based in ONTARIO or QUEBEC)
4 weeks of vacation + 5 paid personal days annually
Group insurance programs as of your first day, including access to telemedicine and an EAP
Collective RRSP with matching contribution
Internet reimbursement and more