Staff Data Engineer

Job Overview

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.

Job Description

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.

We created Upside to transform brick-and-mortar commerce.

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.

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.

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.

Key Responsibilities

• About the role: We're looking for a Staff Data Engineer to serve as a technical leader on the Data Engineering team.
• You’ll lead cross-functional workstreams, shape patterns and architecture across teams, and elevate the overall quality and impact of data work at Upside.
• 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.
• 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.
• 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.

Required Skills and Qualifications

• 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.
• 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.
• Experience with DevOps practices (e.g., CI/CD for data), data governance, or FinOps (cost-conscious design).
• 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.
• Engineers are encouraged to focus deeply on their work, collaborate effectively with team members, and continuously develop their skills.

Benefits and Perks

• Location: Remote Compensation: The US base salary range for this full-time position is $215,000 - $250,000 + equity + benefits.
• 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!

Work Location and Schedule

This role is listed as Remote USA with location information shown as Remote USA. The employment type is Full Time.

About the Company

Upside is the organization connected with this listing. USA Jobs Today displays this opportunity for job discovery only, so applicants should verify company details, application instructions, and eligibility on the official employer website.