Engineer building scalable data platforms for commercial trucking API company. Designing and optimizing the data platform to tackle complex backend challenges.
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.
Requirements
- 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.
Benefits
- 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
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