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 Solid 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. #J-18808-Ljbffr

📌 Data Platform Engineer Kafka Spark (Toronto)
🏢 Homebase
📍 Toronto