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Upside

Engineering Manager - Analytics Engineering

Posted 2 Hours Ago
Be an Early Applicant
Hybrid
4 Locations
185K-215K Annually
Senior level
Hybrid
4 Locations
185K-215K Annually
Senior level
The Engineering Manager will lead the Analytics Engineering team, manage data platforms, enhance MLOps practices, and improve data accessibility across Upside.
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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 an Engineering Manager to lead our Analytics Engineering team, the owners of Upside’s core data platform. This team provides the ingestion, modeling, orchestration, and tooling capabilities that power analytics and data-driven decisions across the company.

You’ll combine technical acumen with people-first leadership to scale our platform, foster engineering growth, and drive data accessibility and trust across internal teams. This role will also help close a strategic gap in our technical organization by guiding the evolution of MLOps practices to support the development, deployment, and monitoring of machine learning models used in personalization and optimization features.

Here are some ways we have seen leaders drive impact at Upside:

  • Create a safe, collaborative team environment. You name problems and invite open discussion, which motivates your team to do their best work.

  • Operate with a first-team mindset. You lean in when important areas need help, regardless of whether it's “your” domain, and prioritize the success of the whole organization.

  • Raise the bar. You identify and influence improvements in quality, performance, speed of execution, and engineering standards.

  • Grow talent. You coach your engineers, recognize their achievements, and help them develop skills that will benefit them and Upside for years to come.

  • Set clarity and empower autonomy. You ensure expectations and direction are clearly articulated so that individuals and teams can operate with independence, confidence, and creativity.

In addition to the leadership responsibilities above, you will:

  • Co-Create and drive the vision and roadmap for Upside’s data platform, shaping the strategy for data across Upside in alignment with company goals.

  • Ensure our data stack, which includes Snowflake, dbt, and Dagster, enables scalable, self-service, and trustworthy workflows for reporting, analytics, and experimentation.

  • Drive strategic data platform initiatives that improve reproducibility, reliability, and analytics enablement—such as modernizing legacy infrastructure, implementing tools like Snowflake Semantic Views and Cortex, and transforming 3rd-party data into trusted, production-ready assets.

  • Define and track key platform health metrics, including pipeline reliability, SLA adherence, cost-efficiency, and model deployment readiness.

  • Partner cross-functionally with Product, Engineering, Data Science, and GTM stakeholders to ensure the data platform supports current and emerging business needs.

  • Represent Analytics Engineering in company-wide planning forums, technical councils, and cross-functional working groups.

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 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 3+ years of experience managing data, analytics, or ML engineering teams, and at least 3+ years of hands-on experience as an individual contributor building data products, pipelines, or ML systems.

  • Are proficient with modern data platforms and tooling, including Snowflake, dbt, and Dagster, and are fluent in core concepts like modeling, orchestration, and data transformation.

  • Have hands-on experience or deep familiarity with MLOps practices, such as model versioning, deployment pipelines, monitoring, and reproducibility.

  • Thrive in environments where you’re asked to scale teams, elevate systems, and bring clarity to ambiguity.

  • Are comfortable designing and reviewing solutions in AWS environments, and make thoughtful tradeoffs to balance performance, cost, and maintainability.

  • Are eager to integrate generative AI tools into development workflows to accelerate delivery and improve the developer experience.

  • Communicate clearly across technical and non-technical audiences, and can advocate effectively for platform investments that support long-term business value.

Engineering Culture
We want our engineering leaders to have the time to coach and enable growth for their engineers as well as the space to make thoughtful and impactful technical decisions. We ask our managers to focus on a team of around 8 direct reports, while our more senior managers may operate across two teams. The staffing for these reports is always split - we see incredible value from a mix of full-time and contract staff.

Location:

This hybrid role is based in our Austin, Chicago, DC, or NYC office. In-office attendance is required on Monday, Tuesday, and Thursday and may increase based on project-based needs and changes to Upside’s in-office policy over time.

Compensation:

The US base salary range for this full-time position is $185,000 - $215,000+ 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 [email protected].

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.

Top Skills

AWS
Dagster
Dbt
Snowflake

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