Cohere jobs. checked todayCohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems.Skills, with evidenceAirflow / orchestration orchestrate it in Airflow and Cloud Run must haveDepth in data modeling: you think in fact and dimension tables must haveYou’ll lead the team that makes Cohere’s data trustworthy, governed, and available must havedbt model the data warehouse in dbt must haveGovernance & security Own data governance. Define how humans, service accounts, and agents get access to governed data must have not practised hereTerraform Everything is provisioned as code in Terraform must have not practised hereAWS Production experience with cloud data warehouses (Big Query, Snowflake, or similar) not practised hereGCP Production experience with cloud data warehouses (Big Query, Snowflake, or similar) not practised hereWarehousing As the head of the Data Foundation pillar of our Analytics and Data Insights team, you’ll lead the team that makes Cohere’s data trustworthy, governed, and available:



the warehouse every analytics surface runs on, the pipelines that keep it fresh, the access model that keeps it secure, and the agentic analytics layer that lets anyone at Cohere (and their agents) ask questions of governed data direSQL You’ll run ingestion into Big Query from internal and external data sources, orchestrate it in Airflow and Cloud Run, model the data warehouse in dbt, and serve the results through Looker, export APIs, and customer-facing analytics surfaces.SQL You’ll run ingestion into Big Query from internal and external data sources, orchestrate it in Airflow and Cloud Run, model the data warehouse in dbt, and serve the results through Looker, export APIs, and customer-facing analytics surfaces. not practised hereThis role is both highly visible and highly impactful, and you’ll inherit a solid structure on which to build the rest of the stack: a Terraform-provisioned warehouse framework, dbt modeling conventions, an alerting and incident-response practice, and documentation patterns to keep everything discoverable.#J-18808-Ljbffr

📌 Senior Staff Data Engineer Staff (Toronto)
🏢 D8 LooP
📍 Toronto