Data Engineering Manager

Relay is a digital banking platform that gives self-made business owners the tools and know-how to be great with money—bringing clarity, confidence, and control to every dollar earned, so they can turn hard work into lasting success. We do this by replacing financial guesswork with real visibility, transforming cash flow from a constant source of stress into a clear signal owners can use to run stronger, more resilient businesses.

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.

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  We're looking for people who are relentless, curious, and care deeply about the work. You're encouraged to apply even if your experience doesn't perfectly match the job description -- your perspective and drive matter more. We welcome diverse backgrounds and people who think critically, challenge the status quo, and want to help small businesses thrive.

  If you require accommodations at any stage of the hiring process, please reach out to your Talent Partner.

  Disclaimer: For compliance reasons, all offers of employment at Relay are conditional upon a successful background check and employment verification through Certn.

  Important Notice: Relay’s recruitment team only contacts candidates and corresponds from official corporate email addresses ending in @relayfi.com. We will never ask for sensitive personal data (such as bank account details, credit card numbers, or social security/insurance numbers) during the initial application or interview stages.

• 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.

Experience with:

• AWS or GCP

• Dagster or another data orchestrator

• Fivetran and Hightouch

• Terraform

• Kafka or other real-time data infrastructure