Software Engineer, Strategy Research Analytics
Build and evolve reliable analytics infrastructure, pipelines, schemas, and foundational datasets supporting quantitative research across strategies. The role requires strong Python and SQL skills, distributed data-platform experience, and ownership of observability, performance, and reproducibility.
About the job
Responsibilities
- Own implementation and ongoing operation of recurring analytics pipelines, including Airflow DAGs, 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 foundational analytics tables and metrics with strong schema discipline and reproducible computation.
- Define and implement reliability standards, including SLOs, observability patterns, runbooks, incident response, and postmortems.
- Improve transparency and usability through documentation, discoverability, schema contracts, metadata, and data lineage.
- Optimize distributed compute and SQL query performance; design partitioning and file-sizing strategies for columnar storage.
- Mentor engineers through design reviews and promote operational and data-modeling rigor.
Requirements
- Bachelor’s degree in Computer Science or equivalent professional experience.
- 3+ 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 robust data-governance principles.
Preferred Qualifications
- Experience leading architectural migrations or major data-platform refactors.
- Familiarity with AWS cloud technologies and on-premises compute clusters, including Slurm, SSH, and Unix.
- Exposure to quantitative research or machine-learning environments.
Compensation and Benefits
- Competitive compensation and benefits package.
- Daily catered lunches.
- Technology talks from company experts.
Skills
Python, SQL, Airflow, Presto, Spark, Parquet, Orc, AWS, Slurm, Unix, Data Modeling, Data Lineage, Metadata Management, Data Governance, Schema Design
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