We at Predict42 are the "AI-first" B2B SaaS scale-up behind the MIGO Feedback Hub. We transform scattered feedback for global market leaders into actionable knowledge – with AI as the true core of our product, rather than just a trendy feature.
As we transition from a startup to an enterprise scale-up, we are looking for an experienced Data Engineer (m/f/d) with a strong data warehousing background to structurally reinforce our platform team. In this role, you will ensure operational reliability, optimize our data architecture, and lay the foundation for our strategic milestones.
Responsibilities
- DWH & Data Modeling: You shape, build, and operate high-performing data warehouse structures and analytical models natively optimized for Google BigQuery.
- SQL Transformations: Design, develop, test, and optimize complex, maintainable, and high-performance SQL-based data models using Dataform, dbt, or comparable transformation frameworks.
- Migration Projects: Contribute directly to the modernization of our data platform and drive the migration of existing data warehouse workloads from ClickHouse to BigQuery—including data models, transformations, pipelines, and validation.
- Data Pipelines & Semantic Layer: You engineer robust, fault-tolerant ingestion and ETL/ELT pipelines and model a consistent semantic data layer for reliable downstream data delivery.
- Testing & Standards: Establish and continuously improve automated testing, data validation, and monitoring standards across all data pipelines.
- Software Best Practices: Apply modern software engineering practices—such as version control, code reviews, CI/CD, and automated testing—to elevate our data workflows.
Qualifications
- Experience: 1 to 3 years of professional experience in data engineering, data warehousing, or a similar role. You work highly independently and thrive when taking on real responsibility.
- Focus on SQL & Data: Strong SQL skills for crafting complex queries, modeling analytical layers, and handling large datasets with ease.
- Python & Automation: Practical experience using Python to implement pipelines, automate operational processes, and replace recurring manual tasks.
- Cloud & Tools: Sound hands-on experience with Google BigQuery in a production environment, as well as practical experience with Dataform or a comparable SQL transformation framework (e.g., dbt).
- Engineering Mindset: Solid foundation in Git-based workflows, CI/CD, and automated quality checks, paired with a pragmatic approach focused on reliability and maintainability.
- Language: German (B2 Minimum) and fluent English (written and spoken) for seamless collaboration in our international team.
Benefits
- Learning Opportunities: Cutting-edge data engineering projects, mentorship, and clear career advancement in a fast-scaling AI environment.
- Competitive Compensation: Competitive salary, comprehensive benefits, and virtual stock options.
- Agile Culture: Collaborative young team in a fun, high-energy working environment.
- Impactful Work: Build the critical data backbone of our LLM-powered platform, directly contributing to innovative enterprise solutions.
Gehalt: 3.879,11€ - 5.233,92€ pro Monat
Leistungen:
- Firmenevents
- Flexible Arbeitszeiten
- Homeoffice-Möglichkeit
- Kostenlose Getränke
- Kostenloser Parkplatz
Arbeitsort: Vor Ort
