Analytics Engineer, Data Platform

Upside; Washington (District of Columbia); On-site; USD 149,000 - 180,000; Full time

Benefits offered by this job

Medical/Dental/Vision

Equity (ISOs)

401(k)

Parental leave

Wellness membership

Mental health support

Unlimited PTO

Flexible work environment

Lunch reimbursement

Employee Resource Groups

Learning stipend

Transparent culture

Amazing mission

Job summary

Upside is seeking a Data/Analytics Engineer in Washington, DC to own dbt models, optimize data pipelines, and provide trustworthy analytics for marketing, product, and data teams. You will design, test, and monitor models, write design docs, and turn vague asks into concrete work.

You should have 3–5 years in data or analytics engineering, strong SQL, Python, and experience with dbt, Snowflake, and orchestration tools. Join a collaborative team that values clear docs and mentorship.

Qualifications

• 3–5 years in data or analytics engineering.
• Fluent in SQL and comfortable with complex joins.
• Experience owning dbt models in a version-controlled repo.
• Python for orchestration, transformations, and tests.

Responsibilities

• Own a scoped domain of dbt models: design, build, test, ship, and monitor them, with a clear point of view on how they should be structured
• Turn ambiguous asks from Marketing and Product into scoped work, and talk openly about tradeoffs when the ask and the timeline don't fit together
• Write the design doc for the features you own and break the work into pieces teammates can pick up
• Add monitoring and alerting to your models so your team catches problems before stakeholders do
• Take your turn on our support rotation, debug what breaks, and prevent the repeat
• Leave behind runbooks, schema docs, and diagrams that make your work easy for the next person to own
• Coach engineers earlier in their careers on the team, in code review and day to day

Skills

Analytics experience

SQL proficiency

Python knowledge

Tools

dbt

Snowflake

Dagster

Data warehouse

Job description

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.

The work

Five million people use Upside to earn cash back on gas, groceries, and dining. The offers they see, the lifecycle messages they get, and the partner launches behind both all run on data models. You'll own a set of those. Not just building them. Deciding how they should be shaped, testing them, monitoring them, and documenting them well enough that someone else can safely build on your work. You'll sit close to Marketing, Data, and MarTech, so a lot of the job is turning a messy question into something concrete and trustworthy. Team of six. Snowflake, dbt, Dagster, AWS.

What You'll Do In Your First Year

• Own a scoped domain of dbt models: design, build, test, ship, and monitor them, with a clear point of view on how they should be structured
• Turn ambiguous asks from Marketing and Product into scoped work, and talk openly about tradeoffs when the ask and the timeline don't fit together
• Write the design doc for the features you own and break the work into pieces teammates can pick up
• Add monitoring and alerting to your models so your team catches problems before stakeholders do
• Take your turn on our support rotation, debug what breaks, and prevent the repeat
• Leave behind runbooks, schema docs, and diagrams that make your work easy for the next person to own
• Coach engineers earlier in their careers on the team, in code review and day to day

You might be a good fit if

• You've spent around 3–5 years in data or analytics engineering, or you've done comparable work under a different title
• You're fluent in SQL, comfortable with window functions and complex joins, and you think about query performance without being asked
• You've owned dbt models in a version-controlled repo; conventions, tests, CI, and the occasional cleanup of someone else's tangle
• You know Python well enough to work in orchestration, transformations, and tests
• You have an opinion on modeling tradeoffs (dimensional vs. one big table) and can explain which you'd pick and why
• You can explain a technical decision to a marketer and an engineer in the same meeting, and adjust how you say it for each
• You've worked in Snowflake, or a comparable warehouse you could translate from

Nice To Have, Not Required

• Marketing, growth, or lifecycle data: events, attribution, experimentation, or tools like Braze, Iterable, or Segment
• Dagster, Airflow, or another modern orchestrator
• CI/CD for data, data governance, or cost-conscious warehouse design
• Supporting ML workflows, like building features or watching model inputs
• Making warehouse data usable by AI tooling; semantic layers, data contracts, or documentation that agents and humans can both read

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 [e-mail].

This email is for accessibility accommodations only, it should not be used to submit job applications.

Compensation Range: $149K - $180K