MLOps / Data Engineer

Job summary

The MLOps Data Engineer bridges data science and production systems, building reliable infrastructure that turns listener data into structured, machine-readable signals for automated advertising. The role designs machine-learning CI/CD pipelines, optimizes distributed Apache Spark processing, manages Databricks environments, and productionizes models through APIs or batch workflows. It also supports monitoring, testing, reproducibility, and scalable audience data feeds for programmatic audio advertising.

Benefits

Qualifications

• Experience in data engineering, MLOps, and DevOps focused on automation and scalability
• Strong Python skills and hands-on Apache Spark experience
• Advanced Databricks expertise, including Delta Lake, Structured Streaming, and feature engineering
• Knowledge of CI/CD principles and tools
• Familiarity with AWS, Azure, or GCP for data and machine-learning workloads
• Ability to evaluate cost, performance, scalability, and maintainability trade-offs
• Experience with Kubernetes or OpenShift, including deployment, scaling, and fault tolerance
• Advanced English proficiency
• IAB standards, programmatic advertising infrastructure, or AdTech data pipeline familiarity is an asset
• Must be based in Ontario or Quebec

Responsibilities

• Design, implement, and maintain CI/CD pipelines for machine-learning workflows
• Build and optimize Apache Spark pipelines for large-scale listener datasets
• Deploy and manage Databricks environments, clusters, and scheduled jobs
• Productionize machine-learning models in scalable APIs or batch systems with data scientists
• Implement automated pipeline testing, monitoring, and alerting
• Maintain version control, model registries, and reproducible environments
• Develop structured, queryable listener data feeds for automated buying systems

Skills

Languages

Industry

Relocation