Lead Data Engineer

Lead 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

We're looking for a Lead Data Engineer to join Stream on our mission of elevating the quality of apps for billions of users globally. You'll be the technical owner of the data platform our go-to-market and product decisions run on.

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

What you'll work on

You'll own the pipelines, integrations, and central repository that bring Stream's data together, and the models that turn it into something the business can trust.

A Revenue Operations team owns the stakeholder relationships and business questions, so your time goes into building durable systems rather than chasing requirements.

Analytics translation is increasingly handled by AI, which is exactly why the engineering underneath it matters. Strong data modeling is at the core of this role.

We're mid-migration to GCP, so there's real architecture to shape and own.

Job responsibilities:

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, and lead incident response when data is stale, wrong, or late. 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.

Set technical direction: define engineering standards and architecture, review pipeline and model changes, and mentor the engineers and analysts who contribute to the platform.

About you

You like owning a platform end to end and staying hands-on while you do it.

You're comfortable in a small team and a fast, unfinished environment, and you're energized by building rather than by growing a large org around you.

You lead through the work: architecture, code review, and mentoring, not a management title.

You have:

6+ years building and operating production data platforms