About Katalyze AIKatalyze AI is a quick-growing AI-driven biotech platform company on a mission to make life-saving drugs accessible and affordable for everyone. Our AI Agents help pharmaceutical and biotech companies increase production efficiency, reduce costs, and minimize waste. We're a team of humble, fast-moving, and curious craftspeople working at the intersection of science and AI.About the RoleWe're looking for a Staff or Senior Data Engineer to own the data infrastructure that powers Katalyze AI's platform. You'll make architecture decisions, design integrations with customer data systems, and build the streaming pipelines that give our AI models and agents access to clean, reliable, real-time data — setting the patterns the team builds on as we scale.What You'll DoOwn the data infrastructure architecture — define standards, patterns, and tooling decisions for the data layerDesign and build data integration pipelines connecting customer systems (MES, LIMS, ERP, historians) to the Katalyze AI platformDevelop and operate real-time and batch data streaming infrastructure (Kafka, Kinesis, or similar) at scaleBuild and maintain ETL/ELT pipelines for structured and unstructured scientific dataEstablish data quality, reliability, and observability frameworks across all pipelinesCollaborate with ML and Data Science teams to deliver clean,



well-structured data for model training and inferenceDesign data schemas and storage solutions (data lakes, warehouses) optimized for AI/ML workloadsWork directly with customer IT teams during deployments to establish secure data connections and meet compliance requirementsSet technical direction for the data engineering function as the team growsWhat We're Looking For7+ years of data engineering experience, with a track record of owning systems — not just building within themDemonstrated experience making architecture decisions: choosing tools, designing schemas, defining standardsDeep expertise in data streaming (Kafka, Kinesis, Flink, or Spark Streaming) — designed and operated in production, at scaleStrong proficiency in building data integrations with external enterprise systems (REST APIs, OPC-UA, proprietary connectors)Experience with cloud data platforms (AWS Glue, Databricks, Snowflake, or similar)Proficiency in Python and SQL; experience with dbt or similar transformation toolingStrong data quality and observability instincts — you've built frameworks, not just used existing toolsBackground in industrial data systems (OSIsoft PI, Ignition, MES/LIMS integrations) is a strong plusComfortable communicating technical tradeoffs to non-technical stakeholders

📌 Staff Data Engineer (Toronto)
🏢 Katalyze AI
📍 Toronto