Senior Software Engineer, Strategy Research Analytics

Responsibilities

• In addition to hands-on implementation, you will shape technical direction, establish reliability standards, and drive consolidation efforts that improve consistency, scalability, and reproducibility across research analytics systems.
• Stabilize existing analytics pipelines to ensure critical data is available for our data scientist and research partners
• Implement monitoring/alerting and operational runbooks; participate in incident response and postmortems
• Standardize outputs from strategy workflows into a unified analytics schema (tables, metrics definitions, partitioning strategy)
• Improve dataset discoverability via documentation, schema contracts, and metadata/lineage primitives
• Optimize query performance and cost for distributed engines (Presto/Spark) and columnar formats (Parquet/ORC)
• 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

Preferred

• 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.

Preferred Qualifications

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Equal Opportunity Employer

The Voleon Group is an Equal Opportunity employer. Applicants are considered without regard to race, color, religion, creed, national origin, age, sex, gender, marital status, sexual orientation and identity, genetic information, veteran status, citizenship, or any other factors prohibited by local, state, or federal law.