Senior Software Engineer - Distributed Systems
HybridZürich, Zurich, Switzerland
Job Summary
Own, design, and operate end-to-end pandas and Apache Spark pipelines within Databricks or confidential computing enclaves, taking full responsibility from development through production monitoring. Improve and productionize machine learning models for audience targeting and campaign measurement while building robust validation, exhaustive test coverage, and self-healing jobs to guarantee reliability. Collaborate cross-functionally with data scientists and backend engineers to ship features, leveraging AI-powered productivity tools to raise quality standards. Profile, benchmark, and tune Spark workloads to drive continuous improvement in orchestration and observability.
Required Qualifications
- Bachelor/Master/PhD in Computer Science, Data Engineering, or a related field
- 5+ years of professional experience
- Expert-level Python
- hands-on experience with pandas
- PySpark/Scala Spark
- distributed-data processing
- Proven track record building resilient, production-grade data pipelines
- rigorous data-quality and validation checks
- Experience running workloads in Databricks
- Spark on Kubernetes
- other cloud/on-prem big-data platforms
Desired Qualifications
- Working knowledge of ML lifecycle
- model serving
- familiarity with techniques for audience segmentation
- look-a-like modelling
- Exposure to confidential computing
- secure enclaves
- homomorphic encryption
- similar privacy-preserving tech
- Rust proficiency
- Data-platform skills: operating Spark clusters
- job schedulers
- orchestration frameworks (Airflow, Dagster, custom schedulers)
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