Quant jobs / Balyasny Asset Management

Data Engineer, Multi-Asset Arbitrage

The multi-asset arbitrage data team builds the research data platform used by portfolio managers. This engineer owns large-scale ingestion, storage and access for backtests and related applications.

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.

Design petabyte-scale data ingestion and backfills
Build efficient research-data queries and APIs
Control historical and streaming data quality
Tune storage and processing performance

What they ask for

Required

Five or more years of data-intensive engineering
SQL and time-series databases
Python, Rust or C++
Dataframe processing
Batch and streaming ETL
Parquet/Arrow storage
Distributed-system debugging

Preferred

ClickHouse or Snowflake
Financial applications
Data APIs
Distributed tracing

Education: No degree requirement is specified.
Experience: 5+ years building data-intensive systems or backtesting infrastructure.
Languages and tools: Python
Rust
C++
SQL
Parquet
Arrow
Kafka
Redis

How to prepare

Build a versioned time-series store suitable for backtests
Compare columnar formats and query performance
Design monitoring for a streaming research-data pipeline

What to study

The HFT Quant Developer roadmap sets out the stages for this kind of role, with free resources for each.

Open the roadmap

Apply

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

View the posting on Balyasny Asset Management’s site ↗

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