Voleon
Software Engineer, Strategy Research Analytics
About this role
Lead the design and operation of Voleon's analytics infrastructure supporting research strategies, owning critical pipelines and datasets while modernizing fragmented workflows into a standardized, scalable platform. Collaborate with data scientists and researchers to ensure reliable, consistent analytics systems that drive research velocity.
What you'll do
- Own implementation and ongoing operation of recurring analytics pipelines with monitoring, alerting, and reliability improvements
- Lead architectural evolution including schema standardization, DAG consolidation, and modernization of legacy workflows
- Build and maintain base analytics tables with strong schema discipline and reproducible computation
- Define and implement reliability standards (SLOs, observability patterns, runbooks) across analytics pipelines
- Optimize distributed compute and SQL query performance; design data layouts for columnar storage
- Mentor engineers through design reviews and establish operational rigor standards
What they're looking for
- Python
- SQL
- Distributed query engines (Presto/Spark)
- Data modeling and schema design
- Airflow or similar workflow orchestration
- Metadata management and data lineage
- Columnar storage formats (Parquet/ORC)
- Data governance and observability
Benefits
- Highly competitive compensation package
- Beautiful modern office with daily catered lunches
- Technology talks by AI/ML experts
- Collegial working environment with internationally recognized researchers
- Strong technical ownership in mission-critical role
- Remote work opportunity
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Voleon
Voleon is an AI-driven asset manager that builds data infrastructure and production systems to support research and trading workflows. The company is hiring Software Engineers, Site Reliability Engineers, and End User Support Engineers to scale its technology platform and support its operations.
- Website
- voleon.com
Likely interview questions
- Walk us through a large-scale analytics pipeline you've owned end-to-end—how did you approach reliability and monitoring?
- Describe your experience migrating or consolidating fragmented data systems. What were the key technical and organizational challenges?