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About the Role
Join the Innovation team to rapidly validate new data initiatives end-to-end. You will prototype representative connectors and pipelines, generate performance readouts, and deliver handoff packages for productization.
Responsibilities
- Prototype ingestion and connector patterns using NiFi, Kafka, and CDC approaches.
- Design adoptable schemas and data models with clear semantics.
- Build incremental lakehouse datasets and produce queryable outputs for performance evaluation.
- Implement data quality checks, metadata hooks, and operability standards.
- Containerize and deploy prototypes on Kubernetes.
- Create adoption artifacts including schemas, reference implementations, and technical design notes.
Requirements
- 3+ years of data engineering experience with pipeline delivery.
- Strong proficiency in Python and SQL.
- Practical knowledge of streaming and CDC fundamentals.
- Experience with the Kafka ecosystem.
- Familiarity with lakehouse storage and query layers.
- Experience working in Kubernetes and container environments.
- Eligible to work in Germany.
- EU or NATO citizenship preferred.
- Subject to export-control screening.
Skills
- Python
- SQL
- NiFi
- Kafka
- Kafka Connect
- Kafka Streams
- CDC
- Hudi
- Iceberg
- Delta
- Kubernetes
- Trino
- Hive
- Postgres
Location
- Germany
- Berlin
Work Type
- Remote-first
- Full-time
Experience Level
- 3+ years
Benefits
- 30 days vacation
- Equipment budget
- Learning budget
- Regular Berlin prototyping sprints
About the Company
- Orcrist builds the Orcrist Intelligence Platform (OIP), a Kubernetes-based data intelligence system.
- Provides SaaS, self-hosted, and air-gapped deployment options.
- Supports mission-critical customers with search, ML enrichment, and investigative workflows.