Data Engineer

SuiteSpot is a PropTech company transforming how residential real estate is managed and operated at scale. Our award-winning Maintenance and Capital SaaS solutions serve the top 50 multifamily property management operators in North America, helping them streamline operations across hundreds of thousands of units. We move fast, ship real solutions, and measure ourselves by customer outcomes. Our engineering team operates with high autonomy and direct customer impact. We live by P.I.E.—Passion, Integrity, and Execution—and look for people who do the same. The Role We're hiring a Data Engineer to build and maintain the data products our enterprise customers consume. Our customers run large multifamily portfolios and want SuiteSpot's operational data flowing into their own data lakes and warehouses, usually Snowflake. You'll build and maintain the customer-facing data model in Snowflake, set up data sharing into their environments, and develop the Power BI semantic models, reports, and dashboards embedded in our product. Most of the work is in Snowflake and Power BI, with the occasional customer call to walk through schema questions or gather requirements. You'll report into engineering and work closely with Customer Success, Delivery, and the product team. What You'll Do

Snowflake Platform: Implement and maintain the customer-facing data model in Snowflake. Build the entities our customers consume, keep them versioned and documented, and roll out changes without breaking downstream consumers

Data Sharing and Exports: Design and operate data sharing from SuiteSpot into customer Snowflake environments, with external exports when needed

Power BI Development: Build Power BI semantic models, reports, and dashboards embedded in our product.

Snowflake: You've built and operated Snowflake workloads in production, including sharing, warehouses, streams and tasks, and resource monitors.

SQL: Strong fundamentals, comfortable with CTEs, window functions, and complex aggregations. You know when SQL is the right tool and when it isn't.

Data pipelines: You understand how operational data gets into a warehouse (CDC, backfills, schema evolution) well enough to participate in design conversations and propose changes at an architectural level.