aiomatic builds a digital maintenance assistant that reduces unplanned downtime through predictive maintenance.
It continuously analyzes machine data, detects anomalies early, and notifies teams with clear, actionable context.
As part of the Application Engineering team, you’ll take ownership of our data storage and warehouse foundations (schemas, performance, reliability, and access patterns), while also shipping production-grade backend services and RESTful APIs that power our customer application and anomaly review workflows.
Location: Hamburg (hybrid).
You must be based within commutable distance to Hamburg, as one weekly on-site day is part of the role.
Tasks Data Storage Ownership: Own the foundations of our data storage layer, including schema design, migrations, performance tuning, and reliability.
Data Modeling: Design clear, scalable schemas and data marts for analytics and product use cases.
Backend Services: Develop backend services that expose storage-backed capabilities to the product.
RESTful APIs: Design, implement, and maintain APIs with strong contracts, versioning, and observability.
Quality & Operations: Improve test coverage, performance, and reliability through monitoring and thoughtful alerting.
Collaboration: Work closely with product and engineering to translate.
Requirements Experience: 5+ years of professional software development experience, with substantial time in data engineering.
Core Expertise: Strong expertise in Python and SQL.
Data Storage: Hands-on experience owning a database or warehouse, including schema design, performance, reliability, and access patterns.
Warehouse: Experience with analytics-oriented storage and modeling (e.
, data marts) and a pragmatic approach to cost and performance.
Backend: Experience building backend services in Python.
Database Layer: Hands-on experience with ORM tools, especially SQLAlchemy.
APIs: Strong experience designing and implementing RESTf.