Senior Data Engineer
Own and evolve Stream’s revenue operations data platform, including ingestion, transformation, modeling, infrastructure, reliability, and reverse ETL. The role requires 5+ years of production data platform experience, strong SQL and Python, cloud warehouse expertise, and modern ELT and infrastructure-as-code skills.
About the job
Responsibilities
- Build and evolve ingestion pipelines using Python and dltHub into BigQuery, integrating Salesforce, Stripe, Postgres, PostHog, cloud billing, and other go-to-market systems.
- Design incremental loading, write dispositions, scheduling, and predictable source onboarding.
- Build SQLMesh transformation models and maintain accurate dimensional models for revenue waterfall, GTM funnel, marketing attribution, and product usage.
- Improve data quality and observability through freshness checks, reconciliation tests, and execution monitoring.
- Own BigQuery and supporting GCP infrastructure, including Terraform, IAM, service accounts, scheduled jobs, and deployment workflows.
- Deliver trusted datasets to Looker Studio, Google Sheets, and internal CRM systems; run reverse ETL into operational systems such as Salesforce.
- Shape engineering standards and architecture, review pipeline and model changes, and support analysts and engineers contributing to the platform.
- Respond to stale, incorrect, or delayed data and trace issues across pipelines, transformations, and upstream systems.
Requirements
- 5+ years building and operating production data platforms.
- Expert SQL and strong Python skills.
- Experience designing incremental, idempotent, and well-tested pipelines.
- Strong experience with BigQuery or another modern cloud data warehouse.
- Experience with modern ELT tools such as SQLMesh, dbt, dltHub, Fivetran, or Airbyte.
- Experience with orchestration and CI/CD, such as GitHub Actions or Airflow.
- Infrastructure-as-code experience with Terraform or an equivalent tool.
- Strong data modeling skills, including dimensional modeling, warehouse design, testing, and observability.
Nice-to-haves
- 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.
- Experience working with business stakeholders while maintaining engineering discipline.
- Deep GCP experience, including IAM, service accounts, and BigQuery cost optimization.
Compensation and Benefits
- Colorado salary range: $150,000–$180,000 per year, plus stock options.
- Hybrid work with three days per week in the office.
- 19+ days of paid time off and 10 paid holidays.
- Health, dental, and vision coverage; 401(k) contribution plan with 4% match.
- Fitness stipend, learning and development budget, parental leave, company laptop, parking and transit benefits, and other office perks.
Skills
Python, SQL, BigQuery, GCP, Sqlmesh, dbt, Dlthub, Terraform, Airflow, GitHub Actions, Data Modeling, Salesforce, Stripe, Posthog, Looker Studio
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