Quant jobs / Voleon

Senior Software Engineer – Strategy Research Analytics

A senior data-infrastructure engineering role inside the research engineering group of a machine-learning-driven investment manager. You would own the analytics pipelines and datasets used by researchers across strategies.

What you’d work on

Our reading of the posting: what a new hire in this role would most likely spend their first months on.

Run and improve recurring analytics pipelines such as Airflow jobs
Standardise strategy outputs into a unified analytics schema
Add monitoring, runbooks and reliability standards
Tune distributed query performance on Presto/Spark and columnar formats
Improve data documentation, lineage and discoverability

What they ask for

Required

6+ years building analytics or data infrastructure
Python and SQL
Distributed query engines and large-scale compute
Data modelling, schemas and partitioning
Metadata, lineage and governance
Ownership of critical data systems

Preferred

Leading platform migrations
AWS and on-prem clusters (Slurm, Unix)
Exposure to quant research or ML environments

Education: Bachelor's in computer science or equivalent professional experience
Experience: 6+ years in analytics or data infrastructure
Languages and tools: Python
SQL

How to prepare

Build an Airflow pipeline that writes partitioned Parquet research tables
Practise query tuning in Spark or Presto with large datasets
Design a metrics schema for strategy performance reporting
Learn data lineage and reproducibility practices for research

What to study

Apply

Read the full posting on Voleon’s site before applying: requirements, location and pay can change after we check them.

View the posting on Voleon’s site ↗

SelfMadeQuant wrote this summary from the employer’s public posting, last checked 6 November 2026. SelfMadeQuant isn’t affiliated with Voleon and doesn’t handle applications.