Data Engineering Manager

Relay's data engineering team has tripled in size, from 4 to 12, and is now splitting into two teams. Analytics Data Engineering works close to the business, building the models, pipelines and dashboards that teams use to run the company. Data Platform, the team you'll lead, owns the foundation underneath: infrastructure, cost, real-time data, observability, and the AI capabilities the rest of Relay builds on.

The team's north star is platform health. That means a fast, reliable, cost-efficient platform with strong observability, and partners across the company who can do their work without waiting on us.

What You'll Be Doing

• Lead and grow a senior team of data engineers. With an experienced team in place, your role is to provide direction, challenge thinking, and help the team make decisions and move work forward.

• Own Snowflake cost. In your first 90 days, you’ll develop and execute a plan to reduce Snowflake costs month over month, working closely with the team to identify and deliver savings.

• Get data into stakeholders' hands faster. You'll define and drive Relay's approach to real-time data and platform enablement, including streaming (Kafka) and a Snowflake MCP server that opens our data to AI tooling.

• Make platform health visible. Build observability so the team finds a problem before a stakeholder does.

• Translate platform work into business outcomes. You’ll help the team prioritize upgrades, migrations and refactors by linking technical investments to business value, whether that’s driving revenue, improving efficiency or reducing risk.

• Balance speed against technical debt, in both directions. Sometimes you'll persuade the team to ship with some debt because the business value is there. Sometimes you'll persuade the business to give the team more time. You'll know which is which.

• Run the team's operating rhythm. That includes standups, sprint and roadmap planning, architectural decisions, code review, and the requests that come in from across Relay.

Who You Are

• You have at least two years of experience managing engineers, including senior team members with strong technical perspectives and the expertise to back them up.

• You have deep, hands-on production experience with Snowflake and dbt, including building data models.

• You've owned a production data platform, and ideally you've led meaningful improvements to one, such as cutting cost, improving reliability or adding new capability.

• You challenge decisions with curiosity, not authority. You ask why before you ask how long, and you can find a path that serves both the engineer's concern and the business deadline.

• You lead with context. You explain the problem, the metric and the business case before the architecture.

• You're highly fluent with AI tools, both in how you work and in how you'd guide a team building AI-enabled data capabilities.

Bonus Points

Experience with:

• AWS or GCP

• Dagster or another data orchestrator

• Fivetran and Hightouch

• Terraform

• Kafka or other real-time data infrastructure

The Interview Process

• Stage 1: A 45-minute Google Meet video call with a member of our Talent team

• Stage 2: A 60-minute Google Meet video call with the Hiring Manager

• Stage 3: A take-home case study followed by a 60-minute Google Meet video call with our Engineering team

• Stage 4: A 45-minute Google Meet video call with a member of our leadership team

The annual salary range for this role is 207,000 CAD to 253,000 CAD.

For candidates who demonstrate full readiness for the defined scope of the role, the typical starting salary is 230,000CAD. Offers below this point reflect candidates we believe can grow into the full scope of the role with support and development. Offers above this point reflect impact that meaningfully exceeds the role’s defined expectations or an expanded scope from day one.

• You push relentlessly for reinvention: You're always asking "how can this be better?" -- in your work, in your craft, in yourself. Comfort is a signal to push harder, not coast. You'd rather build something better than defend something familiar.