Senior Software Engineer, Strategy Research Analytics

VoleonRemote (USA)FullTime2w ago$200K - $255K

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Job description

About the role

Voleon applies advanced artificial intelligence and machine learning to investment management, operating as a multibillion-dollar asset manager with nearly twenty years at the frontier of quantitative finance. The Senior Software Engineer in Strategy Research Analytics leads the architectural direction and long-term evolution of the analytics infrastructure that powers research reporting and analysis across all core strategies. This position entails ownership of mission-critical recurring pipelines and foundational datasets, steering the migration from fragmented, bespoke workflows toward a standardized, observable, and query-native platform. Collaboration is central, requiring close partnership with Data Scientists, Researchers, and Data Infrastructure teams to guarantee reliable, consistent, and queryable data assets. The role offers significant technical ownership within a high-impact area of the research organization, directly influencing research velocity and the quality of insight generation.

Key facts

Location: Remote (USA)

Engagement: Full-time

Compensation: $200K - $255K base salary per year with bonus eligibility

What you'll do

Own the implementation and ongoing operation of recurring analytics pipelines, such as Airflow DAGs, including the design and maintenance of monitoring, alerting, and reliability improvements to ensure critical data availability for research partners.
Lead the architectural evolution of the analytics platform, driving schema standardization, DAG consolidation, and the modernization of legacy workflows to improve consistency and scalability.
Drive cross-team technical alignment when consolidating duplicated or inconsistent analytics outputs, establishing unified definitions and computation logic across strategy workflows.
Build and maintain base analytics tables and metrics with rigorous schema discipline, ensuring reproducible computation and strong data modeling practices including partitioning strategies.
Define and implement reliability standards such as Service Level Objectives (SLOs), observability patterns, and operational runbooks, adopting these standards across all analytics pipelines and participating in incident response and postmortems.
Improve transparency and usability of data assets through comprehensive documentation, enhanced discoverability tooling, and clear data contracts that govern schema evolution and usage.
Optimize distributed compute performance and SQL query execution for engines like Presto and Spark; design efficient data layouts, partitioning schemes, and file sizing for columnar storage formats such as Parquet and ORC.
Mentor engineers through rigorous design reviews and code reviews, raising the bar for operational excellence, data modeling rigor, and software engineering best practices within the team.
Stabilize existing analytics pipelines to guarantee that critical datasets are consistently available for Data Scientists and Researchers across Voleon's core strategies.
Implement metadata management, data lineage tracking, and robust data governance primitives to support dataset discoverability and auditability.
Collaborate directly with Data Infrastructure teams to integrate analytics systems with broader platform capabilities and shared compute resources.
Translate complex research requirements into scalable, maintainable engineering solutions that balance flexibility for researchers with platform stability.

Requirements

Bachelor's degree in Computer Science or equivalent professional experience demonstrating comparable depth.
Six or more years of professional experience building, operating, and maintaining large-scale analytics or data infrastructure systems.
Strong proficiency in Python for data engineering workflows and SQL for complex analytical querying and data manipulation.
Deep, hands-on experience with distributed query engines (such as Presto, Trino, or Spark) and large-scale compute systems handling petabyte-scale datasets.
Demonstrated history of ownership for large-scale or mission-critical data infrastructure, including on-call responsibilities and reliability engineering.
Expert-level data modeling expertise, encompassing schema design, partitioning strategy, file format optimization, and reproducibility considerations for analytical workloads.
Expertise in metadata management, data lineage systems, and the application of robust data governance principles to enforce data quality and compliance.
Ability to operate effectively in a collaborative, cross-functional environment involving researchers, data scientists, and platform engineers.
Strong communication skills for documenting technical designs, data contracts, and operational runbooks for diverse audiences.

Nice to have

Experience leading major architectural migrations or large-scale refactors of data platforms, including strategy, execution, and stakeholder management.
Familiarity with AWS cloud technologies (e.g., S3, EMR, Glue, Athena) combined with experience operating on-premises compute clusters using schedulers like Slurm and standard Unix/SSH tooling.
Exposure to quantitative research, machine learning model training pipelines, or financial services technology environments.
Prior experience working within a Research Engineering or Data Platform team at a technology-driven hedge fund, asset manager, or similar quantitative firm.
Contributions to open-source data infrastructure projects (Airflow, Spark, Presto, dbt, etc.) or internal platform tooling adopted widely across an organization.

Skills & tools

Python, SQL, Apache Airflow, Presto, Trino, Apache Spark, Parquet, ORC, AWS (S3, EMR, Glue, Athena), Slurm, Unix/Linux, SSH, Git, CI/CD, Data Modeling, Schema Design, Partitioning Strategies, Data Lineage, Metadata Management, Data Governance, SLO/SLI Definition, Observability (Monitoring/Alerting), Distributed Systems, Columnar Storage Optimization, Quantitative Finance Domain Knowledge.

Practical notes

The compensation package includes a base salary range of $200,000 to $255,000 annually, supplemented by bonus eligibility; actual offers vary based on experience, location, and internal equity.
The role is designated as FullTime with a Remote workplace model, allowing the employee to work from anywhere within the United States.
Visa sponsorship details are not explicitly mentioned in the source material; candidates requiring sponsorship should confirm eligibility directly with the recruiting team.
The team sits within Research Engineering and interacts heavily with Data Scientists and Researchers across all core investment strategies, requiring a blend of engineering rigor and research empathy.
On-call participation for incident response and postmortem processes is expected as part of the reliability ownership mandate.
The "Friends of Voleon" referral program offers a $15,000 bonus for successful candidate referrals, subject to specific terms and conditions.
Voleon is an Equal Opportunity Employer committed to a diverse and inclusive workplace.