Lead Data Engineer

About the role

Stream powers real-time Chat https://getstream.io/chat/, Video https://getstream.io/video/, Activity Feeds https://getstream.io/activity-feeds/, and AI Moderation https://getstream.io/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. You will own the end-to-end data platform that brings together pipelines, integrations, and a central repository, shaping the models that the business relies on for forecasting, commissions, pricing, churn analysis, and product insight. You will work closely with a Revenue Operations team that owns stakeholder relationships, allowing you to focus on building durable systems and strong data modeling rather than ad hoc reporting. In this role, you will lead the migration to GCP, defining and owning the architecture while mentoring engineers and analysts who contribute to the platform. Your work will directly influence how the company runs by ensuring the reliability, correctness, and observability of the data foundation.

Key facts

What you'll do

• Build and evolve the ingestion platform using Python and dltHub to load into BigQuery, integrating Salesforce, Stripe, Postgres, PostHog, cloud billing, and other GTM systems while designing incremental loading, write dispositions, and scheduling.
• Design and maintain the transformation layer with SQLMesh models across a layered architecture, creating clean and well-tested dimensional models and establishing clear conventions for grain, naming, and audit.
• Strengthen reliability by expanding data quality and observability, building freshness checks, reconciliation tests, and execution monitoring, and leading incident response when data is stale, wrong, or late.
• Own the platform infrastructure on GCP, including BigQuery and supporting services, plus Terraform, IAM, service accounts, scheduled jobs, and deployment workflows tuned for security, reliability, and cost.
• Enable the business by delivering trusted datasets to Looker Studio, Google Sheets, and our internal CRM, and by running reverse ETL back into operational systems like Salesforce.
• Set technical direction by defining engineering standards and architecture, reviewing pipeline and model changes, and mentoring the engineers and analysts who contribute to the platform.
• Shape the data model to support core business metrics such as revenue waterfall, GTM funnel, marketing attribution, and product usage, ensuring accuracy and trust.
• Drive adoption of modern ELT tooling such as SQLMesh, dbt, dltHub, Fivetran, or Airbyte, and orchestration with GitHub Actions, Airflow, or equivalent.

Requirements

• Bring 6+ years of experience building and operating production data platforms with a strong sense of ownership.
• Write expert SQL and comfortable Python to develop robust, maintainable data pipeline logic.
• Design incremental, idempotent, and well-tested pipelines that handle scale and edge cases gracefully.
• Demonstrate deep experience with BigQuery or another modern cloud data warehouse, including optimization and cost awareness.
• Use modern ELT tooling such as SQLMesh, dbt, dltHub, Fivetran, or Airbyte in production environments.
• Manage orchestration and CI/CD with tools like GitHub Actions, Airflow, or equivalent to automate deployments and testing.
• Apply infrastructure-as-code practices with Terraform to provision and secure GCP resources consistently.
• Show strong data modeling skills, including dimensional modeling, warehouse design, testing strategies, and observability practices.
• Lead technical decisions through architecture, code reviews, and mentoring, without relying on a management title.

Nice to have

• Revenue Operations or GTM data experience that aligns data with commercial outcomes.
• Salesforce and Stripe data modeling, including complex joins and transformations across billing and CRM systems.
• Product analytics platforms such as PostHog, including event-level modeling and behavioral analysis.
• Marketing attribution and funnel analytics, with methods for measuring channel performance and incrementality.
• MRR, expansion, contraction, churn, and revenue reconciliation logic grounded in billing data.
• Experience working closely with business stakeholders while maintaining strict engineering discipline.
• Deep GCP familiarity, including IAM, service accounts, and BigQuery cost optimization techniques.

Practical notes

This is a full-time role based in our Amsterdam office.