Data Engineer

Do you have experience in SQL?, * Experience: 2-3 years of professional experience in Data Engineering. You have a track record of working with BigQuery, or you are an expert in comparable warehouse, e.g. Snowflake looking to master the Google Cloud stack.

• Software Mindset for Data: You believe data transformations are software. You write clean, performant SQL and are a fan of version control and CI/CD for data.
• Cloud Enthusiast: You are comfortable in the Google Cloud (BigQuery, Cloud Storage, Pub/Sub, Cloud Run) or any comparable cloud ecosystem.
• State-of-the-Art Knowledge: You understand modern paradigms like Data Lakehouse architectures and how to build decoupled, scalable data models.
• Mainz-Based: You value in-person collaboration with a high-caliber team and want to be part of the rising tech community in the Rhein-Main region.

Pulled from the full job description

• Employee mentoring program
• Free parking
• Profit sharing
• Pension plan
• Work from home
• Flexible schedule, * Learning & Mentorship: Work directly with our Platform Lead and CTO to master modern data stack principles in an AI-First environment.
• Impactful Work: You aren't just building "reports"-you are building the pipes that make "Zero-Shot Intelligence" possible for world-class organizations.

Predict42 is a Mainz-based B2B SaaS company specializing in Feedback Analytics. Our platform, MIGO, helps global enterprises consolidate scattered feedback into clear business decisions. As we transition from a startup to an Enterprise Scale-Up, we need a motivated Data Engineer to help us migrate to a 100% BigQuery-driven architecture and build the structural foundation for our "AI-First" engine. Your Role & The Tech Stack You will be a key member of the "Platform" team. * Modern DWH Migration: Lead the transition of our legacy warehouse operations to BigQuery, ensuring high performance, partitioning, and cost-optimization. * Declarative Pipelines: Use Dataform to build version-controlled, tested, and reliable SQL-based transformations. * Self-Service BI & Semantic Layers: Model and structure data to be consumed by modern visual dashboards, apis, and chat interfaces. * Data Integrity & Contracts: Implement automated validation layers and Data Contracts to ensure that the data driving critical business decisions is always accurate and "inviolable."