The Voleon GroupRemote
Senior Software Engineer, Strategy Research Analytics
United States of America
Full Time
2 weeks ago
$200,000 - $255,000 USD
H1B Sponsor Likely
Key skills
PythonSQLDistributed query enginesLarge-scale compute systemsData infrastructureData modelingSchema designPartitioning strategyReproducibility in data computationMetadata managementData lineageData governanceAWS cloud technologiesUnix systemsAIMachine LearningAnalyticsAirflowAWS
About this role
Voleon 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 architecture of Voleon’s analytics infrastructure, ensuring reliable analytics systems while collaborating 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