Senior Software Engineer, Strategy Research Analytics

The Voleon Group is a technology company that applies state-of-the-art AI and machine learning techniques to real-world problems in finance. As a Senior Software Engineer in Strategy Research Analytics, you will lead the design and evolution of Voleon’s analytics infrastructure, ensuring reliable and consistent datasets while collaborating closely with Data Scientists and Researchers.

Responsibilities:

• Own implementation and on-going operation of recurring analytics pipelines (e.g., Airflow DAGs) including monitoring, alerting, and reliability improvements
• Lead architectural evolution of the analytics platform, including schema standardization, DAG consolidation, and modernization of legacy workflows
• Drive cross-team technical alignment when consolidating duplicated or inconsistent analytics outputs
• Build and maintain base analytics tables and metrics with strong schema discipline and reproducible computation
• Define and implement reliability standards (SLOs, observability patterns, runbooks) adopted across analytics pipelines
• Improve transparency and usability through documentation, discoverability, and clear data contracts
• Optimize distributed compute and SQL query performance; design data layouts (partitioning, file sizing) for columnar storage
• Mentor engineers through design reviews and raise the bar for operational and modeling rigor

Requirements:

• Bachelor's degree in Computer Science or equivalent professional experience
• 6+ years of experience building and operating analytics or data infrastructure systems
• Strong proficiency in Python and SQL
• Deep experience with distributed query engines and large-scale compute systems
• Demonstrated ownership of large-scale or mission-critical data infrastructure
• Strong data modeling expertise, including schema design, partitioning strategy, and reproducibility considerations
• Expertise in metadata management, data lineage, and applying robust data governance principles
• Experience leading architectural migrations or major refactors of data platforms
• Familiarity with AWS cloud technologies and on-prem compute clusters (e.g., Slurm, SSH, Unix)
• Exposure to quantitative research or machine learning environments