If you’ve worked with Big Data or followed courses on the topic at ETH or elsewhere, you are already aware of the challenges associated with designing pipelines and storage systems that adhere to the core principles of designing data-intensive applications, such as scalability under load, resilience to failure, and adabitibility to change. In this 6-month assistantship (with the possibility of extension), You’ll build real-world systems embodying these principles.

• Data Pipelines: Enhance and extend ETL flows from utilities, weather APIs, and solar monitoring systems-ensuring they’re reliable (think “backpressure handling” and “exactly-once” semantics) and maintainable
• Databases: Work with time-series stores (PostgreSQL/TimescaleDB, InfluxDB) designed for high-volume ingestion and low-latency queries
• Reliability & Recovery: Implement replication, backup, and disaster recovery strategies-making sure the system survives faults without losing data
• Access & Security: Deploy robust role-based access control, integrating OAuth2.0, GitLab, or Keycloak, while complying with ETH regulations
• Visualization & Experimentation: Build dashboards (Grafana, Bokeh) and remote experimentation APIs to give researchers live insight into grid behavior

We are seeking a committed and responsible candidate with a bachelor’s degree (or equivalent) in computer science, electrical engineering, or a related field. Current master’s students are also encouraged to apply.

Required skills and qualifications:

• Strong proficiency in Python and system architecture
• Interest in data engineering, distributed systems, and collaborative problem-solving
• Excellent communication and documentation skills
• Fluency in English (German is a plus)