Data Platform Engineer Kafka Spark
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Build Homebase’s data platform with Kafka, Spark, and Python in a hybrid Toronto schedule requiring Tuesdays and Wednesdays onsite. Own systems powering data and AI features.
As a Data and ML Platform Engineer, you will manage data ingestion, platform infrastructure, model serving, and machine learning foundations. You will work with Databricks, Delta, Terraform, CI/CD, gRPC, MLflow, and feature stores. The role partners across data engineering, data science, and product engineering to move proofs of concept into production.
Key Responsibilities:
- Build and run CDC and streaming pipelines
- Manage Databricks, Unity Catalog, warehouses, and Terraform
- Ship gRPC services and real-time inference workloads
- Evolve feature stores and MLflow practices
- Participate in the team’s on-call rotation
Requirements:
- Production experience with Kafka and CDC systems
- Hands-on Spark and Delta experience
- Strong Python, SQL, and data modeling fundamentals
- Container infrastructure experience with Docker, ECS, or Kubernetes
- Comfort collaborating onsite Tuesdays and Wednesdays in Toronto
Apply distributed systems, infrastructure, and machine learning platform expertise to Homebase’s AI-powered product foundation.