Senior Data Engineer

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.

We’re looking for a Senior Data Engineer to help us scale our data ecosystem as Relay enters an exciting new chapter of growth. This is a unique opportunity to be responsible for key aspects of the evolution of our data and analytics stack as the company grows. You'll have a dedicated interest in ensuring our teams have access to the right data at the right time in order for us to make the best decisions for our customers.

• →

  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 3+ years of Data Engineering experience

• You write SQL that goes well beyond SELECT, WHERE and GROUP BY -- think complex window functions, query optimization, and schema design

• You're fluent in Python and know how to write clean, maintainable, production-grade code

• You have hands-on experience with our core stack: dbt for transformations, Dagster for orchestration, Snowflake as our data warehouse, and cloud infrastructure (AWS, GCP, or Azure)

• You have experience with BI/data visualization tools (Looker, Metabase, Mode, etc.) and understand what it takes to support a great analytics layer

• You have a track record of extracting real value from large, complex datasets -- and a genuine curiosity for what the data is telling you

• You can drive work independently, collaborate well with cross-functional stakeholders, and know when to ask for input vs. just move

• You have an understanding of applied statistics, are able to create quantitative models, and can clearly communicate findings to a technical and non-technical audience

• You have domain knowledge of Banking or SaaS analytics, and are familiar with concepts like LTV, churn, retention, etc.

• You have experience with streaming or microbatch analytics (Spark Streaming, Flink, Beam, etc.) and design methodologies of persistent event stores (AWS Kinesis, GCP PubSub, Apache Kafka, Apache Pulsar, etc.)

• You’ve joined a company at its early stages and have seen it through scale