Upside
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Senior Analytics Engineer I
role at
Upside
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
Analytics Engineer
to join the team responsible for Upside’s core data platform. You’ll play a key role in building trusted data products that serve both internal teams and customer-facing features, while also improving the analytics platform and enabling others to do their best data work.
This is a great opportunity for someone who’s confident working with large datasets and complex business logic, thrives in a fast-moving environment, and wants to grow as a technical contributor while collaborating closely with product managers, analysts, data scientists, and engineers across the company.
Responsibilities
Design and build complex, scalable data products that support internal analytics and power product features, using tools like dbt, Snowflake, and Dagster.
Translate ambiguous business needs into structured, trustworthy data assets—owning development end-to-end, from design through deployment and monitoring.
Contribute to shared platform tooling that improves pipeline orchestration, testing, access control, and observability for both engineers and analysts.
Evaluate and implement new platform capabilities, such as Semantic Views, Cortex, or SnowML, to improve performance, maintainability, and user experience.
Support and enable teammates across the org, including onboarding new users, resolving data issues, and documenting patterns and best practices.
Maintain reliability and data quality through shield support rotations, strong monitoring, alerting, and test coverage.
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 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, with a mindset of continuous improvement and investing in observability, automation, or new infrastructure to reduce toil.
You believe that pulling quality upstream starts with engineering, 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 2+ years of experience in data or analytics engineering roles, preferably in a modern data stack environment (e.g., Snowflake, dbt, Dagster, Airflow).
Are fluent in SQL and comfortable writing performant, modular transformations at scale.
Have working knowledge of Python, particularly in data orchestration, transformations, and testing.
Understand tradeoffs between different modeling approaches and can choose appropriate techniques based on data volume and business needs.
Can independently communicate technical concepts to both engineers and non-technical stakeholders.
Think critically about ROI, know when to automate, and understand how to balance long-term quality with short-term delivery.
Preferred Qualifications
Experience supporting machine learning workflows, such as building features or monitoring model inputs and outputs.
Familiarity with DevOps practices (CI/CD for data), data governance, or FinOps (cost‑conscious design).
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 This hybrid role is based in Austin, Chicago, DC, or NYC. 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 $130,000 - $180,000 + equity + benefits. The final starting pay will be determined based on job‑related skills, experience, qualifications, work location, and market conditions.
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 & 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.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Industries Retail
#J-18808-Ljbffr
Senior Analytics Engineer I
role at
Upside
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
Analytics Engineer
to join the team responsible for Upside’s core data platform. You’ll play a key role in building trusted data products that serve both internal teams and customer-facing features, while also improving the analytics platform and enabling others to do their best data work.
This is a great opportunity for someone who’s confident working with large datasets and complex business logic, thrives in a fast-moving environment, and wants to grow as a technical contributor while collaborating closely with product managers, analysts, data scientists, and engineers across the company.
Responsibilities
Design and build complex, scalable data products that support internal analytics and power product features, using tools like dbt, Snowflake, and Dagster.
Translate ambiguous business needs into structured, trustworthy data assets—owning development end-to-end, from design through deployment and monitoring.
Contribute to shared platform tooling that improves pipeline orchestration, testing, access control, and observability for both engineers and analysts.
Evaluate and implement new platform capabilities, such as Semantic Views, Cortex, or SnowML, to improve performance, maintainability, and user experience.
Support and enable teammates across the org, including onboarding new users, resolving data issues, and documenting patterns and best practices.
Maintain reliability and data quality through shield support rotations, strong monitoring, alerting, and test coverage.
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 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, with a mindset of continuous improvement and investing in observability, automation, or new infrastructure to reduce toil.
You believe that pulling quality upstream starts with engineering, 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 2+ years of experience in data or analytics engineering roles, preferably in a modern data stack environment (e.g., Snowflake, dbt, Dagster, Airflow).
Are fluent in SQL and comfortable writing performant, modular transformations at scale.
Have working knowledge of Python, particularly in data orchestration, transformations, and testing.
Understand tradeoffs between different modeling approaches and can choose appropriate techniques based on data volume and business needs.
Can independently communicate technical concepts to both engineers and non-technical stakeholders.
Think critically about ROI, know when to automate, and understand how to balance long-term quality with short-term delivery.
Preferred Qualifications
Experience supporting machine learning workflows, such as building features or monitoring model inputs and outputs.
Familiarity with DevOps practices (CI/CD for data), data governance, or FinOps (cost‑conscious design).
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 This hybrid role is based in Austin, Chicago, DC, or NYC. 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 $130,000 - $180,000 + equity + benefits. The final starting pay will be determined based on job‑related skills, experience, qualifications, work location, and market conditions.
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 & 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.
Seniority Level Mid‑Senior level
Employment Type Full‑time
Industries Retail
#J-18808-Ljbffr