Upside is a nationally scalable housing stability platform that partners with health plans and employers to identify and stabilize people experiencing housing instability.
Meet Upside: We created Upside to transform brick-and-mortar commerce. Our technology uses the sophistication of online retail—profit measurement, attribution, and incrementality—to provide users with more value on their everyday purchases and brick-and-mortar businesses with new, profitable customers. We’ve helped millions of users earn 2 to 3 times more cashback than any other product, and hundreds of thousands of brick-and-mortar businesses earn measurable profit. Billions of dollars in commerce run through the Upside platform every year, and that value goes directly back to our retailer partners, the consumers they serve, and important sustainability initiatives. Meet Upside: We created Upside to transform brick-and-mortar commerce. Our technology uses the sophistication of online retail: profit measurement, attribution, and incrementally to provide users with more value on their everyday purchases and brick-and-mortar businesses with new, profitable customers. We've helped millions of users earn 2 to 3 times more cashback than any other product, and hundreds of thousands of brick-and-mortar businesses earn measurable profit. Billions of dollars in commerce run through the Upside platform every year, and that value goes directly back to our retailer partners, the consumers they serve, and important sustainability initiatives. About the role: We're looking for a Principal Data Engineer to be the technical backbone of our Analytics Engineering team. You'll architect and evolve the data platform that powers Upside's most critical product and business decisions: setting patterns, leading cross-functional workstreams, and raising the bar for how data moves through the company. This is a role for someone who wants real ownership. Our team is small and intentional, our scope is large (~2,000 tables, 100 pipelines), and the work directly shapes product features, ML models, and business outcomes. If you do your best work when the problem is ambiguous and the impact is visible, this is the role for you. Here are some ways you'll drive impact - Lead platform modernization; deprecate legacy workflows, migrate pipelines to scalable patterns, and sharpen our CI/CD and developer experience - Drive infrastructure and FinOps initiatives across Snowflake, Dagster, and dbt; reducing cost, improving governance, and increasing maintainability - Own platform evolution projects like making data consumable by agentic tools and workflows, and improving orchestration across the analytics stack - Design and deliver complex, domain-critical data products used by analysts, data scientists, and product teams to ship features and drive strategy - Architect reusable, extensible patterns for modeling, orchestration, and transformation; balancing flexibility, cost, and long-term maintainability - Lead technical planning across cross-functional teams, breaking down large data initiatives into scoped, sequenced workstreams - Mentor engineers, build internal documentation and tooling, and raise the overall standard for analytics engineering at Upside - Partner with engineering, product, data science, and business stakeholders to deliver end-to-end solutions - Represent Data Engineering in design forums and shape the future roadmap for data at Upside Why You Should Apply This role is a good fit for you if: - You challenge the status quo when it makes the team and business better and use data to make the case - You thrive at the intersection of systems and storytelling; building robust solutions and communicating their purpose so others can act confidently - You build for resilience and scale, and know when to invest in observability, automation, or new infrastructure to reduce toil - You believe quality starts upstream; you champion early testing, validation, and a culture of getting it right before it breaks downstream Ideal Qualifications - 8+ years in data or analytics engineering with a track record of owning complex, business-critical systems end to end - Hands-on experience with AWS; deployments, workload management, cloud infrastructure and the modern data stack (Snowflake, dbt, Dagster, Databricks, Terraform) - A track record of leading platform migrations, deprecations, or upgrades across shared systems; balancing technical risk, continuity, and long-term maintainability - Ability to design secure, reusable patterns for data ingestion, access control, and platform automation and comfort partnering with Infrastructure, Security, and Governance stakeholders - Experience with DevOps practices (CI/CD for data), data governance, or FinOps - Ability to break down ambiguous, cross-functional problems and lead implementation from design to deployment - Clear communication across all audiences; engineers, analysts, product managers, and business leaders - A genuine drive to mentor others, set standards, and leave every system better than you found it Preferred Qualifications - Experience supporting ML workflows; building features or monitoring model inputs and outputs - Background in a fast-growing startup or on platform-style teams that serve internal customers Engineering Culture: We want our engineers to have the time and support to grow in their craft and contribute meaningfully to impactful technical decisions. Engineers are encouraged to focus deeply on their work, collaborate effectively with team members, and continuously develop their skills. Teams are thoughtfully staffed to create a dynamic and diverse environment that enhances learning and innovation. Location: Remote Compensation: The US base salary range for this full-time position is $215,000 - $250,000 + equity + benefits. The final starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. Your recruiter can share more about the specific salary range during the hiring process. Benefits: - Medical, dent