Turn large-scale listener data into production intelligence with Databricks, Delta Lake, structured streaming, and feature engineering. Work fully remotely within Canada.
As an MLOps / Data Engineer, you will productionize machine learning models supporting digital audio advertising platforms. You will manage Databricks environments, build distributed pipelines, and collaborate with data scientists on scalable APIs and batch-processing systems. Your work will support structured, machine-readable audience signals.
Key Responsibilities:
- Maintain Databricks infrastructure and schedule production jobs
- Optimize distributed processing using Spark, PySpark, and Scala
- Collaborate with data scientists on model deployment
- Support continuously available,
machine-readable data feeds
- Evaluate infrastructure performance, scalability, and maintainability
Requirements:
- Advanced Databricks experience including Delta Lake
- Experience with structured streaming and feature engineering
- Solid Python skills and hands-on Apache Spark experience
- Cloud familiarity across AWS, Azure, or Google Cloud
- Experience deploying workloads with Kubernetes or OpenShift
Use Databricks, Spark, and machine learning engineering skills to shape dependable data infrastructure for advertising systems.