Role overview

Cohere is a security-first enterprise AI company building foundation models and end-to-end products for real-world business applications. As Senior Staff Data Engineer, you will lead the Data Foundation pillar of the Analytics and Data Insights team, responsible for making Cohere’s data trustworthy, governed, and accessible across the organization. You’ll oversee the complete data lifecycle, from ingestion through serving, ensuring the infrastructure supports both human analytics and agentic systems.

Key responsibilities

Build and lead a team of data and infrastructure engineers, setting technical standards and developing leadership capability within the organization.
Own and sequence the Data Foundation roadmap, including warehouse buildout, agentic analytics programs, data governance initiatives, and platform work that enables other teams.
Design and maintain the end-to-end data platform spanning ingestion from internal and external sources, orchestration in Airflow and Cloud Run, warehouse modeling in BigQuery with dbt, and serving through Looker, export APIs, and semantic layers.
Define and enforce data governance practices including VPC service controls, IAM patterns, access documentation, audit logging, and compliance-critical data request handling.
Operate the alerting and anomaly-detection framework, own data freshness SLAs, lead incident response and postmortems, and establish durable standards to prevent recurrence of failures.
Lead development of an internal analytics agent with evaluation harness, determining where AI automation delivers value in production analytics and data engineering work.
Partner across the organization with product and engineering teams on analytics surfaces, Business Insights on business-facing data marts, Security on governance, and Legal on compliance matters.

Requirements

10+ years of experience in data engineering, data infrastructure, or analytics platform work, with a proven track record leading data platform or infrastructure teams.
Strong hands-on background in data engineering or infrastructure, capable of reading and understanding Terraform plans, dbt DAGs, and Airflow scheduler logs to ask meaningful technical questions.
Production experience with cloud data warehouses such as BigQuery or Snowflake, workflow orchestration tools like Airflow, and infrastructure-as-code tooling like Terraform.
Deep expertise in data modeling with understanding of fact and dimension tables, raw/core/mart layer separation, semantic layers, and where testing and contracts belong in the architecture.
Demonstrated ability to set team roadmaps from company strategy and deliver outcomes that span teams, backed by cross-functional partnerships and executive alignment.
Operational excellence track record including reliable alerting systems, met SLAs, thorough incident investigation, and postmortems that create teachable standards.
Experience with data security and governance practices including IAM, access management, and VPC service controls.

What makes this role worth considering

You’ll work at a global technology company headquartered in Toronto with offices in London, New York City, San Francisco, Montreal, Paris, Berlin, and Seoul. The role is highly visible and impactful, built on a solid foundation including an existing Terraform-provisioned warehouse framework, dbt modeling conventions, and incident-response practices that you can extend rather than build from scratch.