Data Engineer

At Superchat, we're rebuilding how businesses talk to their customers. The phone call, the contact form, the support ticket: all of it is being replaced by messaging and AI. We're building the platform that runs underneath.

Founded in 2020, Superchat has become the platform of choice for 10,000+ businesses worldwide, from globally recognized brands like Allianz, Auto1, Enpal, Danone, and GASAG to the small businesses, dental practices, and one-person startups that need to look bigger than they are. Today, millions of messages flow through Superchat every single day.

We started as a unified inbox: one place for every channel a customer might pick, WhatsApp, email, SMS, Instagram. Then ChatGPT happened, and the second chapter began: AI agents that respond across chat, email, and voice at the quality of the best human teams.

We're 100 people, profitable, and have raised €18M in funding (last round 4.5 years ago, we've been growing on our own money since). Headquartered in Berlin.

We're hiring our first Data Engineer to own Superchat's data platform end to end, from raw product and business data to the gold tables the whole company reports on. Our engineers have already built the foundations, including a warehouse, pipelines, dbt and reverse ETL. Now we need someone to make the platform trustworthy at scale, with testing, monitoring, clear modelling layers and customer history over time. You'll set the standards for how data is modelled and documented, and work with a Business Analyst to build the gold tables that Finance, Sales, Marketing and Product rely on.

Who We Want

An experienced Data Engineer.
You bring 3+ years of building and running data pipelines in production, ideally at a SaaS company. You've owned a data platform, or a large part of one, and you're comfortable making the architecture calls yourself.

Strong in SQL and dbt.
You write and review complex SQL with ease. You've built dbt projects with layered models, tests, documentation.

At home in the Cloud.
You have worked with Data Warehouses in the Cloud, ideally AWS Redshift. BigQuery or Snowflake is also fine.

Reliability-minded.
You think in tests, freshness checks, idempotent loads and backfills. You want to know the data is wrong before a stakeholder tells you.

Curious about the business.
You want to know what MRR, churn or an "active workspace" really mean, and you model data so those definitions hold everywhere they're used. Experience with subscription billing or product usage data is a plus.