Data Engineer

Own and evolve Stream’s end-to-end revenue operations data platform. Build Python and dltHub ingestion pipelines, SQLMesh transformation models, dimensional data models, quality and observability systems, and GCP infrastructure centered on BigQuery. Integrate GTM systems, enable trusted analytics and reverse ETL, improve reliability and cost efficiency, and establish engineering standards. The role requires hands-on platform ownership in a fast-moving hybrid Boulder startup environment. The summary above was generated by AI Senior Data Engineer, Revenue Operations

About Stream

Stream powers real-time Chat, Video, Activity Feeds, and AI Moderation for billions of end-users across thousands of apps, from Strava and Bumble to eBay and Patreon. Our platform processes billions of API requests per month and supports applications with millions of concurrent users, while delivering highly reliable, low-latency services and a great developer experience.

The role

The data platform in this role is what our go-to-market and product decisions run on.

You’ll own the pipelines, integrations, and central repository that bring Stream’s data together, plus the models that turn it into something the business can trust. We’re mid-migration to GCP, so there’s real architecture to shape.

Two things make this different from most data jobs. A Revenue Operations team owns the stakeholder relationships and the business questions, so your time goes into building durable systems instead of chasing requirements. And analytics translation is increasingly handled by AI, which is exactly why the engineering underneath it has to be right. Data modeling is the core of this role.

It’s a small team and a fast, unfinished environment. High drive, sometimes hectic. If you like owning a platform end to end, that’s the appeal., * Build and evolve the ingestion platform. Python/dltHub pipelines loading into BigQuery, integrating Salesforce, Stripe, Postgres, PostHog, cloud billing, and other GTM systems. Design incremental loading, write dispositions, and scheduling, and make onboarding a new source predictable and low-risk.

• Build the transformation layer. SQLMesh models across our layered architecture, clean and well-tested dimensional models, and clear conventions for grain, naming, and audit. Keep the core business models accurate: revenue waterfall, GTM funnel, marketing attribution, and product usage.
• Improve reliability. Expand data quality and observability, build freshness checks, reconciliation tests, and execution monitoring. Take point when data is stale, wrong, or late, and trace issues across pipelines, transformations, and upstream systems.
• Own the platform infrastructure. BigQuery and supporting GCP, plus Terraform, IAM, service accounts, scheduled jobs, and deployment workflows, tuned for security, reliability, and cost.
• Enable the business. Deliver trusted datasets to Looker Studio, Google Sheets, and our internal CRM, and run reverse ETL back into operational systems like Salesforce.
• Raise the technical bar. Help shape engineering standards and architecture, review pipeline and model changes, and share context with the analysts and engineers who contribute to the platform.

You like owning a platform end to end and staying hands-on while you do it. You’re comfortable in a small team, and you’re energized by building rather than by growing an org around you. You influence through the work: architecture, code review, and clear conventions, not a title.

You have:

• 5+ years building and operating production data platforms
• Expert SQL and strong Python
• Experience designing incremental, idempotent, well-tested pipelines
• Solid experience with BigQuery or another modern cloud data warehouse
• Experience with modern ELT tooling such as SQLMesh, dbt, dltHub, Fivetran, or Airbyte
• Experience with orchestration and CI/CD (GitHub Actions, Airflow, or equivalent)
• Infrastructure-as-code experience with Terraform or a close equivalent
• Strong data modeling skills: dimensional modeling, warehouse design, testing, and observability

Bonus points:

• Revenue Operations or GTM data experience
• Salesforce and Stripe data modeling
• Product analytics platforms such as PostHog
• Marketing attribution and funnel analytics
• MRR, expansion, contraction, churn, and revenue reconciliation logic
• Working closely with business stakeholders while keeping engineering discipline
• GCP depth, including IAM, service accounts, and BigQuery cost optimization

• Your work powers forecasting, commissions, pricing, churn analysis, product insight, and board reporting. The quality of your engineering shows up directly in how the company runs.
• The stack is modern and AI-forward: Python, dlt, SQLMesh, BigQuery, Terraform, GitHub Actions, with Claude, Cursor, and Linear across the team.
• You inherit a foundation that already works, built from scratch, so you evolve and harden it rather than start from zero.

You’ll thrive here if

• You want a broad, ambiguous platform to own and the autonomy to make calls on it
• You ship fast and learn fast, even when things are unfinished
• You’re comfortable working with teammates across time zones

You probably won’t if you want tightly scoped tickets, a fully defined process before acting, or a slow and highly predictable environment.

Why join Stream?

We’re a Series B company with global presence and a team of around 145 people from more than 35 countries. We’re backed by Felicis Ventures, GGV Capital, 01 Advisors, Techstars, and Arthur Ventures, with angels including Dick Costolo (ex-CEO of Twitter), Olivier Pomel (CEO of Datadog), Tom Preston-Werner (co-founder of GitHub), and Nicolas Dessaigne (co-founder of Algolia).

We’ll be straight with you: a startup is more demanding than a large company. There’s no fixed playbook, you’ll own things end to end, and you’ll sometimes pick up work outside your title. That’s also what makes it a fast place to grow. If you want real ownership and high scale more than structure and a set career ladder, you’ll feel at home here. What we offer

• 19+ days of paid time off plus 10 paid holidays
• Hybrid work flexibility (3 days a week from the office)
• Free health insurance for the employee and partial coverage for dependents (80% contribution coverage for health and 100% for dental and vision)
• 401k contribution plan with 4% match
• Fitness stipend
• Company equity
• Dog-friendly office!
• A Macbook Pro provided
• A Learning and Development budget
• Team lunches and plenty of snacks
• RTD pass + free parking pass on Pearl Street
• An office on Pearl Street in downtown Boulder
• 12 weeks paid parental leave for primary parents
• The opportunity to attend or present to global conferences and meetups
• The possibility to visit our office in Amsterdam

Note: this list of benefits applies to Colorado-based employees and is adjusted per your location of residence.

Salary (for Colorado only): Our salary ranges are based on national averages. We have wide ranges so we can be flexible and determine compensation based on a number of factors including the candidate’s skills, level of experience, and location.

For Colorado-based candidates we offer a salary $150,000 to $180,000 per year, plus stock options. Final offer within this range depends on experience and interview outcome.

Located on Boulder’s Pearl Street pedestrian mall, our office is steps from popular restaurants and a few miles from hiking trails. We also have an office in Amsterdam where Stream was started, and many employees work remotely globally. More than 25 nationalities collaborate on Stream’s products!