About this role.
Upside is seeking a Staff Data Engineer to provide technical leadership for foundational data products and its analytics platform. The role leads modernization, migration, governance, FinOps, orchestration, and developer-experience initiatives across technologies such as Snowflake, dbt, Dagster, Databricks, Terraform, and CI/CD systems. This engineer will architect scalable patterns, deliver complex domain-critical data products, and coordinate cross-functional work from design through deployment. Success requires strong end-to-end ownership, sound judgment on maintainability and cost, and the ability to mentor peers and influence engineering, product, data science, and business stakeholders. The position is remote, with compensation specifically described for the US market.
Role DNA
A quick view of the complexity, pace, ownership and collaboration implied by the job description.
Job Complexity
5/5Pace & Pressure
4/5Autonomy Level
5/5Communication Load
5/5Salary analysis
Estimated compensation compared with the broader US market for similar roles.
Core skills
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Sample interview questions
I began with an inventory of dependencies, data contracts, service-level expectations, and rollback requirements. I then created a phased migration plan with parallel validation, automated reconciliation checks, clear ownership, and stakeholder communication. This approach allowed the team to preserve continuity while incrementally retiring legacy components.
I would define opinionated defaults for naming, testing, lineage, documentation, access controls, and deployment, while exposing well-governed extension points for domain-specific requirements. Shared templates and CI checks would make the preferred path easy to adopt. I would measure adoption, reliability, runtime, and developer feedback to refine the standards.
I would establish cost attribution by team and workload, monitor warehouse utilization and expensive query patterns, and set appropriate resource monitors and lifecycle policies. I would also optimize models and orchestration schedules, right-size compute, and prioritize incremental processing where appropriate. Cost controls should be paired with service-level metrics so savings do not create reliability or latency regressions.
I advocate for explicit data contracts, schema validation, freshness checks, source-level observability, and automated tests integrated into deployment workflows. Partnering early with source-system owners helps define ownership and expected behavior before pipelines are built. When incidents occur, I use root-cause analysis to improve the upstream controls and prevent recurrence.
I tailor the level of detail to the audience while keeping the decision transparent. For engineers, I provide tradeoffs, diagrams, operational implications, and implementation guidance; for nontechnical stakeholders, I focus on business outcomes, risks, cost, timing, and measurable success criteria. I document the decision and invite feedback early so stakeholders understand both the rationale and their role in adoption.
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 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.
About the role:
We’re looking for a Staff Data Engineer to serve as a technical leader on the Data Engineering team. In this role, you’ll drive the design and implementation of foundational data products and analytics platform capabilities that power Upside’s most critical product and business use cases. You’ll lead cross-functional workstreams, shape patterns and architecture across teams, and elevate the overall quality and impact of data work at Upside.
This role is ideal for someone who enjoys deep technical problem-solving, cares about quality and long-term maintainability, and is motivated by helping others work more effectively with data.
Here are some ways we have seen data & analytics engineers drive impact at Upside:
Lead platform modernization efforts across the analytics ecosystem, such as deprecating legacy workflows and tooling, migrating pipelines to more scalable patterns, and improving the infrastructure, CI/CD, and developer experience
Drive high-leverage infrastructure and FinOPs initiatives across systems like Snowflake, Dagster, and dbt, reducing cost, improving governance, and increasing the scalability and maintainability of Upside’s data platform
Own platform evolution projects such as making data more consumable by agentic tools and workflows, or improving orchestration tooling for analytics workflows.
Design and deliver highly complex, domain-critical data products used by analysts, data scientists, and product teams to unlock new product features, ML models, and strategic decisions.
Architect scalable, extensible patterns for modeling, orchestration, and data transformation, balancing flexibility, reusability, and cost-efficiency.
Lead technical planning and delivery across cross-functional teams, breaking down complex data initiatives into scoped, sequenced workstreams implemented by you and others.
Drive platform adoption and best practices, mentoring other engineers, building internal documentation and tooling, and raising the overall bar for analytics engineering across the company.
Influence upstream and downstream teams, partnering with engineering, product, data science, and business stakeholders to align on requirements and deliver end-to-end solutions.
Represent Data Engineering in technical design forums and contribute to roadmap discussions that shape the future of data at Upside.
Why You Should Apply
This role is a good fit for you if:
You aren’t afraid to challenge the status quo when it makes the team and business better. You learn from those around you while utilizing data to advocate for informed change.
You thrive at the intersection of systems and storytelling, not only building robust solutions but also communicating their purpose, impact and rationale, so teams can experiment, iterate, and act confidently.
You care about building resilient systems that scale. You bring a mindset of continuous improvement, and know when to invest in observability, automation, or new infrastructure to reduce toil and improve outcomes for the team and end users.
You believe that pulling quality upstream starts with engineering. You champion best practices, encourage early testing and validation, and work closely with peers to build a culture of quality from the ground up.
Ideal Qualifications
Have 8+ years of experience in data or analytics engineering, with a track record of owning complex, business-critical data systems end to end.
Have deep experience with the modern data stack (e.g. Snowflake, dbt, Dagster, Databricks), terraform, and cloud infrastructure, and can use those systems to improve performance, reliability, security, and developer experience at scale.
Have a track record of leading platform migrations, deprecations, or upgrades across shared systems, balancing technical risk, operational continuity, and long-term maintainability.
Can design secure, reusable patterns for data ingestion, access control, and platform automation, and are comfortable partnering with Infrastructure, Security, and Governance stakeholders to implement them.
Experience with DevOps practices (e.g., CI/CD for data), data governance, or FinOps (cost-conscious design).
Can break down ambiguous, cross-functional data problems and lead the implementation from design to deployment, collaborating across technical and non-technical teams.
Proactively identify opportunities to improve the analytics platform and are comfortable designing and implementing impactful, reusable solutions.
Communicate clearly across audiences, from engineers and analysts to product managers and business leaders.
Understand how to balance business value, maintainability, and platform standards in your design decisions.
Are excited about the opportunity to mentor others, set standards, and leave systems better than you found them.
Preferred Qualifications
Experience supporting machine learning workflows, such as building features or monitoring model inputs and outputs.
Experience working in a fast-growing startup environment 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, dental, and vision coverage starting on Day 1
Equity (ISOs)
401(k) program
Family planning programs + paid parental leave
Physical fitness and wellness memberships
Emotional and mental health support programs
Unlimited PTO + 10 paid federal holidays + our annual, week-long Winter Break
Flexible work environment
Lunch reimbursement for in-office employees
Employee Resource Groups
Learning and Development stipend
Transparent culture
Amazing mission!
Diversity and Inclusion:
Diversity drives innovation, and our differences make us stronger. We‘re passionate about building a workplace that represents a variety of backgrounds, skills, and perspectives, and we do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. Everyone is welcome here!
If there’s anything we can do to support a disability or special need during your application or interview process, please email accommodations@upside.com.
This email is for accessibility accommodations only, it should not be used to submit job applications.
Notice To Recruiters And Placement Agencies:
This is an in-house search with a dedicated recruiter. Please do not submit resumes to any person or email address at Upside. Upside is not liable for, and will not pay, placement fees for candidates submitted by any party or agency other than its approved recruitment partners.
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