Lead Data Engineer

Stream; Amsterdam; On-site; EUR 120,000 - 160,000; Full time

Benefits offered by this job

Generous compensation

Company equity

28 days paid time off + Dutch holidays

Pension scheme

Learning and development budget

Commute coverage: NS card or company‑b

Fitness stipend

MacBook Pro and peripherals

Catered team lunches and snacks

Office in Amsterdam

Strong team to learn from

Job summary

Stream is seeking a Lead Data Engineer to own the data platform powering Revenue Operations. This full-time role is based in our Amsterdam office, focusing on building durable data pipelines, modeling, and trusted datasets for GTM decisions.

You will lead architecture and mentoring while working in a fast, hands-on environment. Expect collaboration across Salesforce, Stripe, Postgres, and analytics tools, with a modern cloud-first stack and a focus on reliability and cost awareness.

Qualifications

• 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 ELT tooling: SQLMesh, dbt, dltHub, Fivetran, or Airbyte.
• Experience with orchestration and CI/CD (GitHub Actions, Airflow).
• Infrastructure-as-code with Terraform.
• Strong data modeling: dimensional modeling, warehouse design, testing, observability.
• Track record of technical leadership through architecture, code reviews, and mentoring.

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 and onboarding of new sources.
• Build the transformation layer: SQLMesh models across layered architecture with well-tested dimensional models and conventions.
• Improve reliability: data quality, observability, freshness checks, reconciliation tests, and incident response.
• Own the platform infrastructure: BigQuery, Terraform, IAM, service accounts, scheduled jobs, deployment workflows.
• Enable the business: deliver trusted datasets to Looker Studio, Google Sheets, and internal CRM; run reverse ETL to Salesforce.
• Set technical direction: define engineering standards and architecture, review changes, mentor engineers and analysts.

Skills

Production data platforms

Expert SQL

Python

Incremental pipelines

Data modeling

Technical leadership

BigQuery

ETL tooling

Orchestration/CI/CD

Terraform

Tools

BigQuery

dbt

dltHub

Fivetran

Airbyte

SQLMesh

GitHub Actions

Airflow

Terraform

Job description

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
• 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.

Equal opportunity employer statement: Stream provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

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.