Senior Staff Software Engineer - Batch and Realtime Streaming

Summary

Join Voleon, a leading technology-driven firm in finance, as a Senior/Staff Software Engineer. You will play a key role in developing and maintaining Voleon’s Batch and Realtime Streaming platform, the core data infrastructure for our machine learning and trading systems. Collaborate with researchers and finance professionals to design high-performance interfaces and tools. This role offers a significant impact at the intersection of cutting-edge technology and quantitative finance. The team is collaborative, encouraging innovation and efficient execution. Voleon provides a competitive compensation and benefits package, including regular technology talks, a modern office, and daily catered lunches.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field (or equivalent experience)
• 5+ years of software engineering experience, with a strong background in backend systems, distributed computing, or data infrastructure
• Experience in programming languages such as Python, Go, and C++
• Understanding of database technologies (Postgres, MySQL, Cassandra, DynamoDB, SQLite, DuckDB or MongoDB) and experience with APIs (REST/gRPC)
• Strong problem-solving skills, with a focus on delivering high-quality, maintainable, and well-documented solutions
• Excellent communication and collaboration skills; ability to work closely with both engineering and research teams

Responsibilities

• Architect, design, and implement core components for a Batch and Realtime Streaming platform, including data ingestion pipelines, storage systems, serving layers, and API interfaces
• Ship new features by collaborating across research, legal, trading, finance operations data, and infra teams for trading systems
• Collaborate with ML researchers and data scientists to understand their workflows and design intuitive interfaces (APIs, SDKs, UIs) for seamless feature discovery, access, and reuse
• Ensure data quality, consistency, and lineage for features, building robust mechanisms for versioning, monitoring, and governance
• Optimize data pipelines and storage for high performance, scalability, and reliability, considering both batch and real-time use cases
• Drive adoption of the feature store across teams by producing documentation, onboarding materials, and developer support
• Mentor junior engineers and contribute to team best practices and technical excellence

Preferred Qualifications

• Experience building large-scale data pipelines and storage systems (e.g., Airflow, Spark, etc)
• Exposure to modern Python data science tooling. (pandas, polars, dask, duckdb etc)
• Experience with monitoring and observability tools for distributed systems (e.g., Prometheus, Grafana, ELK Stack)
• Prior experience working with feature stores (e.g., Feast, Hopsworks, or custom solutions) is highly desirable

Benefits

• Medical, dental and vision coverage
• Life and AD&D insurance
• 20 days of paid time off
• 9 sick days
• A 401(k) plan with a company match