SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Upside transforms brick-and-mortar commerce by applying online retail sophistication—profit measurement, attribution, and incrementality—to drive value for consumers and retailers. Five million users earn cashback on gas, groceries, and dining through the platform, which processes billions in commerce annually.
You'll own a scoped domain of dbt models within a six-person team, responsible for design, build, test, deployment, and monitoring. The role bridges Marketing, Data, and MarTech, requiring you to translate ambiguous business questions into concrete, trustworthy data solutions. You'll design and document features, break work into manageable pieces for teammates, implement monitoring and alerting, participate in support rotation, and mentor earlier-career engineers.
Key responsibilities include: owning dbt models in version control with clear conventions and testing; turning Marketing and Product asks into scoped work with transparent tradeoffs; writing design docs and breaking features into implementable pieces; adding monitoring to catch issues before stakeholders; debugging production issues and preventing recurrence; creating runbooks and schema documentation; and coaching junior team members.
The tech stack includes Snowflake, dbt, Dagster, and AWS. You'll need 3–5 years in data or analytics engineering, fluency in SQL (window functions, complex joins, query optimization), hands-on dbt experience, Python proficiency for orchestration and transformations, and the ability to explain technical decisions to both marketers and engineers. Experience with marketing/lifecycle data, modern orchestrators, data governance, or ML workflows is valued but not required.
