Senior Staff Data Engineer

Description

The company builds foundation AI models and end-to-end products that help enterprises solve business problems, with a focus on security. It trains and deploys frontier models for enterprises building AI systems.

The team is made up of researchers, engineers, designers and others who care deeply about their work, and each person contributes to the capability of the models and the value they create for customers.

The company is headquartered in Toronto, with offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul.

This role leads the Data Foundation pillar of the Analytics and Data Insights team. The team makes company data trustworthy, governed and available: the warehouse that all analytics runs on, the pipelines that keep it current, the access model that keeps it secure, and an agentic analytics layer that lets staff and their agents query governed data directly.

The team owns the full data lifecycle, from ingesting internal and external sources into BigQuery, to orchestrating jobs in Airflow and Cloud Run, to modeling the warehouse in dbt and serving results through Looker, export APIs and customer-facing analytics. Infrastructure is provisioned as code in Terraform, and governance is built into the design through VPC service controls, IAM patterns and documented access paths.

You will inherit a working foundation: a Terraform-provisioned warehouse framework, dbt modeling conventions, an alerting and incident-response practice, and documentation patterns. The roadmap includes scaling that framework across the company, building an internal analytics agent with a real eval harness, and building a self-maintaining system that keeps company knowledge centralized, current and documented.

Responsibilities

• Hire, grow and lead a team of data and infrastructure engineers, set the technical standard, and develop leaders within the team.
• Turn company strategy into the Data Foundation roadmap, covering the warehouse buildout, the agentic analytics program, data governance and platform work that unblocks other pillars. Make the trade-offs and own their cross-functional impact.
• Own the data platform end to end: ingestion through managed connectors and an open-source connector framework, orchestration on Airflow and Cloud Run, BigQuery warehouse modeling with dbt across raw, core and mart layers, and serving through Looker, export APIs and semantic layers. Provision all of it in Terraform.
• Define how people, service accounts and agents get access to governed data. This covers VPC service controls, IAM patterns, onboarding paths, audit logs, and sensitive requests including legal holds, which must be met by their deadlines.
• Run the alerting and anomaly-detection framework, own data freshness SLAs, and lead incident response and postmortems. Turn each incident into a lasting standard that prevents the same class of failure from returning.
• Connect the semantic layer to an internal analytics agent, build the eval harness that measures its accuracy, and decide, based on evals, where AI goes into production. Apply the same rigor to automating data engineering work.
• Set the company-wide analytics standard through the medallion framework, naming conventions and testing patterns your team maintains. Onboard new domains and keep documentation accurate to how the systems really work.
• Work with the product and engineering teams on analytics features shipped in the product, including a customer-facing analytics export. Work with the business insights team on business marts, with Security on governance, and with Legal on compliance-critical data requests.

Requirements

• 10+ years in data engineering, data infrastructure or analytics platform work, with a strong record of managing data platform or infrastructure teams.
• Substantial hands-on experience in data engineering or infrastructure before moving into management, enough to read a Terraform plan, a dbt DAG or an Airflow scheduler log and ask the right questions.
• Production experience with cloud data warehouses such as BigQuery or Snowflake, workflow orchestration such as Airflow, and infrastructure as code such as Terraform.
• Strong data modeling skills: fact and dimension tables, raw, core and mart separation, semantic layers, and a clear view on where tests and contracts belong.
• A track record of setting a team roadmap from company or function strategy and delivering results that span teams, along with the cross-functional relationships to support it.
• Proven operational discipline: alerting you trust, SLAs you meet, and incidents you investigate thoroughly and document so others learn from them.
• Experience with data security and governance, including IAM, access management, VPC service controls or equivalent, and audit and compliance workflows.
• Real interest in AI. You follow the research, form opinions, and want to build the data foundation that an AI company and its agents rely on.
• Comfort with ambiguity, leading a roadmap with several workstreams, and working directly with executives on priorities.
• If some of this does not match your experience exactly, you are still welcome to apply.

Conditions

The role is remote-friendly. There are offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul, with more planned.

Office-based staff get a daily lunch program, snacks, and regular community and social events.

Remote staff who are not near an office can use a co-working benefit to work alongside others in their city.

The company is an equal opportunity employer and welcomes applicants from all backgrounds.

Benefits

• Weekly lunch stipend of $75 or £75, or the equivalent in your local currency.
• Full health and dental coverage, with a separate mental health budget.
• RRSP matching, 401K and a pension scheme.
• 100% parental leave top-up for up to 6 months, for either parent.
• Annual enrichment budget for arts and culture, fitness and wellness, quality time, and a workspace improvement credit.
• Education and learning stipend for conferences, courses and coaching.
• 6 weeks of paid vacation (30 working days).
• Budget for travelling to other offices if you are remote, plus an annual company offsite.
• $500 home office stipend to set up your workspace.