Lead Data Engineer (Revenue Operations)

Stream; Boulder (CO); On-site; USD 140,000 - 200,000; Full time

Benefits offered by this job

Equipment & Tools

Paid Vacation

Stock Options

Health Coverage

Team Outings

Team Lunch

401(k) Plan

Commuter Benefits

Monthly Fitness Stipend

Job summary

Stream is seeking an experienced Data Platform Engineer to own our data platform end-to-end. You will design and maintain ingestion pipelines (Python/dltHub) loading data into BigQuery and integrating Salesforce, Stripe, and Postgres.

You’ll implement SQLMesh-driven transformations and ensure core models like revenue, funnel, and attribution stay accurate. You’ll shape our architecture in a mid-migration to GCP, improve data quality and observability, and collaborate with business stakeholders.

Qualifications

• 5+ years building and operating production data platforms.
• Expert SQL and strong Python.
• Experience with BigQuery and ELT tooling (dbt, Fivetran, Airflow).
• Experience designing incremental, idempotent pipelines.
• Experience with orchestration and CI/CD (GitHub Actions, Airflow).
• Solid data modeling skills: dimensional modeling and warehouse design.
• Ownership mindset for end-to-end platform development.
• IaC experience: Terraform.

Responsibilities

• Own the data platform end-to-end: ingestion, transformation, and delivery.
• Build and evolve ingestion pipelines (Python/dltHub) loading into BigQuery and integrating systems like Salesforce and Stripe.
• Develop the transformation layer using SQLMesh models and maintain core business models (revenue, funnel, attribution).
• Improve reliability with data quality checks, monitoring, and traceability across pipelines and upstream systems.
• Manage platform infrastructure on GCP (BigQuery, IAM, service accounts) and deployment workflows.
• Deliver trusted datasets to Looker Studio, Google Sheets, and CRM, enabling reverse ETL.

Skills

Incremental pipelines

Orchestration CI/CD

ELT tooling

BigQuery

Production data platforms

SQL

Python

Data modeling

Platform ownership

Team player

Architectural influence

Terraform

PostHog

GTM data

Salesforce integration

Stripe data modeling

Marketing analytics

MRR analytics

GCP IAM/BigQuery

Stakeholder collaboration

Tools

GitHub Actions

Airflow

SQLMesh

dbt

dltHub

Fivetran

Airbyte

BigQuery

Job description

• 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

Benefits

• Equipment & Resources: Computers, standing desks, headphones, and other specialized tools are available for you to be successful
• Paid Vacation: Generous time off on top of observing several national holidays
• Stock Options: You get a piece of ownership in Stream. Stock options are granted to all full-time employees
• Health Coverage: We offer comprehensive healthcare, dental, and vision plans, plus generous parental leave (US only)
• Outings and parties: We like to have fun together! Team outings and parties are regular events around here
• Team Lunch and Snacks: Stream provides in-office daily team lunches and a stocked kitchen with tasty snacks and craft coffee
• 401k: Plan for your retirement through the company offered 401k (US only) or the local pension scheme in Amsterdam, to which Stream will make a contribution
• Commuter Benefits: Employees receive free Office parking and transportation benefits
• Monthly fitness stipend: We value the health and well being of our employees

• Experience designing incremental, idempotent, well-tested pipelines
• Experience with orchestration and CI/CD (GitHub Actions, Airflow, or equivalent)
• Experience with modern ELT tooling such as SQLMesh, dbt, dltHub, Fivetran, or Airbyte
• Solid experience with BigQuery or another modern cloud data warehouse
• 5+ years building and operating production data platforms
• Expert SQL and strong Python
• Strong data modeling skills: dimensional modeling, warehouse design, testing, and observability
• 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
• Infrastructure-as-code experience with Terraform or a close equivalent
• Product analytics platforms such as PostHog
• Revenue Operations or GTM data experience
• Salesforce and Stripe data modeling
• Marketing attribution and funnel analytics
• MRR, expansion, contraction, churn, and revenue reconciliation logic
• GCP depth, including IAM, service accounts, and BigQuery cost optimization
• Working closely with business stakeholders while keeping engineering discipline