Opportunity

Staff Data Engineer – $250K + Equity at Upside in Columbus

Location Columbus
Company Upside
Source jobicy
Posted 2026-09-01 14:23:53

Career & Market Insight

Compensation vs. Market: The $215K–$250K base range for a Staff Data Engineer is competitive and aligns with the upper tier for this level at well-funded US tech companies. Top-tier companies (FAANG) may offer slightly more in total comp via RSUs, but Upside's ISO equity adds meaningful upside for a growth-stage company. This is a strong offer for a non-FAANG environment.

Career Development Signals: This role sits at the Staff level — a key inflection point between senior IC and principal/director tracks. You'll develop highly marketable skills:

  • Modern data stack mastery: Snowflake, dbt, Dagster — all in high demand across data-heavy industries.
  • Cross-functional technical leadership and platform architecture — skills that open doors to Staff/Principal roles at larger companies.
  • FinOps and data governance experience, increasingly critical as data costs scale.
  • ML pipeline integration — a growing area bridging data engineering and ML engineering.

Culture & Stage Signals: Upside is a growth-stage startup (processing billions in commerce) with a lean, impact-focused engineering culture. The emphasis on mentorship, documentation, and raising the bar suggests a maturing engineering org — less chaos than early-stage, but more ownership than enterprise. Green flag: explicit encouragement to challenge the status quo.

Watch For: Staff roles at startups can have broader scope than at larger companies, which is a double-edged sword — high impact, but potential for context-switching. The call for "platform modernization" suggests some legacy technical debt to navigate.

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.

Ways 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 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 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:

  • 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.
  • 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:

  • 8+ years of experience in data or analytics engineering, with a track record of owning complex, business-critical data systems end to end.
  • Deep experience with the modern data stack (e.g., Snowflake, dbt, Dagster, Databricks), Terraform, and cloud infrastructure.
  • Track record of leading platform migrations, deprecations, or upgrades across shared systems, balancing technical risk, operational continuity, and long-term maintainability.
  • Ability to design secure, reusable patterns for data ingestion, access control, and platform automation; comfortable partnering with Infrastructure, Security, and Governance stakeholders.
  • Experience with DevOps practices (e.g., CI/CD for data), data governance, or FinOps (cost-conscious design).
  • Ability to break down ambiguous, cross-functional data problems and lead implementation from design to deployment.
  • Proactively identifies opportunities to improve the analytics platform and implements impactful, reusable solutions.
  • Communicates clearly across audiences—from engineers and analysts to product managers and business leaders.
  • Understands how to balance business value, maintainability, and platform standards in design decisions.
  • 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 + annual week-long Winter Break
  • Flexible work environment
  • Lunch reimbursement for in-office employees
  • Employee Resource Groups
  • Learning and Development stipend
  • Transparent culture

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 [email protected].

This email is for accessibility accommodations only and 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.

Frequently Asked Questions

Is this Staff Data Engineer role fully remote?
Yes, Upside lists this position as fully remote. The compensation is in USD, suggesting the role is scoped for US-based candidates.
What is the salary range for this role?
The US base salary range is $215,000–$250,000 per year, plus equity (ISOs) and a full benefits package. Final pay depends on skills, experience, and location.
What data stack experience is required for this position?
Upside uses a modern data stack including Snowflake, dbt, Dagster, and Databricks, along with Terraform and cloud infrastructure. Deep hands-on experience with these tools is expected.
How much experience is needed to qualify for this role?
Upside is looking for candidates with 8+ years of experience in data or analytics engineering, with a track record of owning complex, business-critical data systems end to end.
Does Upside offer equity as part of the compensation?
Yes, equity in the form of ISOs (Incentive Stock Options) is included in the compensation package alongside the base salary and benefits.
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