Data Engineer

Join Superchat as our first Data Engineer, where you'll own the data platform from raw product and business data to the gold tables used by the entire company. You'll set the standards for data modeling and documentation, work with a Business Analyst to build essential gold tables, and manage ingestion from various tools. You'll also run orchestration, build data quality, capture history, manage the warehouse, and maintain reverse ETL syncs. Enjoy a competitive compensation package, 26 days of paid vacation, and a vibrant start-up culture in the heart of Berlin.

Posséder la plateforme de données de Superchat de bout en bout, en veillant à ce qu'elle soit fiable à grande échelle.

We're looking for people with passion, grit, and integrity. You're encouraged to apply even if your experience doesn't precisely match the description. At Superchat, we welcome diverse perspectives and people who think rigorously

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

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

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

About Superchat

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

Responsibilities

• Définir les normes de modélisation et de documentation des données, et travailler avec un analyste commercial pour construire les tables d'or.
• Gérer l'ingestion des données à partir de diverses sources, concevoir et construire les modèles dbt qui transforment les données brutes en tables d'or.

Requirements

• 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