Divebell is a SaaS platform that seamlessly integrates with databases, file stores, SaaS applications and other sources of structured and unstructured data. The product uses ML and ensemble techniques to classify large quantities of data. It must also solve other data-oriented problems such as sampling and risk estimation. These challenging engineering problems call for an algorithmic approach and a passion for data, security, privacy, and distributed systems. The ideal candidate will have a solid understanding of modern cloud platforms and data integration.

• Kotlin / Java
• Spring
• PostgreSQL
• Relational and non-relational data stores
• Data warehouses and data pipelines
• AWS / GCP / Azure
• Machine Learning
• Docker