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 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: 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

Expert SQL and strong Python

Experience designing incremental, idempotent, well-tested pipelines

Deep 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

Strong data modeling skills: dimensional modeling, warehouse design, testing, and observability

A track record of technical leadership through architecture, code reviews, and mentoring

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

Deep GCP familiarity, including IAM, service accounts, and BigQuery cost optimization

What makes this role exciting

You own the data platform the whole company depends on, not one pipeline or one domain.

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 solid foundation built from scratch, so you get to evolve and harden it rather than start from zero.

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

Generous compensation

Company equity

28 days paid time off plus Dutch public holidays

A pension scheme

A learning and development budget

Commute coverage: an NS business card or a company bike

A fitness stipend

A MacBook Pro and the peripherals you need

Catered team lunches and snacks

An office in the heart of Amsterdam

A strong team to learn from

This list applies to Netherlands-based employees and is adjusted to your location of residence.

Hybrid office policy: applicants based (or relocating to) one of our office locations are expected to work according to the applicable local office attendance policy.

This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Note for external recruiters: We currently have this role covered and do not accept unsolicited agency resumes. We are not responsible for any fees related to unsolicited resumes.