Data Engineer, Multi-Asset Arbitrage

What you'll do

• Design, build, and scale the data plane for back-testing and other data-intensive applications.
• Manage petabyte-level ingestion, ETL processes, data quality, storage, and backfills.
• Develop and maintain APIs to facilitate data consumption by portfolio managers and researchers.
• Architect and build both batch and streaming data pipelines using lakehouse patterns.
• Optimize code performance and tune systems for high-scale distributed applications.
• Implement column-oriented data storage and serialization formats like Parquet or Arrow.
• Build application-level features such as REST APIs to expose core business logic.
• Monitor and trace distributed systems using tools like Prometheus, Grafana, and Sentry.

What we're looking for

• 5+ years of work experience in a data-intensive capacity building back-testing infrastructure or similar initiatives.
• Demonstrable expertise in SQL and databases, specifically time-series and big data stores.
• Proficiency in Python, Rust, or C++ along with at least one data-manipulation library like Pandas, Polars, Dask, Vaex, or PySpark.
• Experience architecting and building data platforms and ETLs using batch, streaming, data lake, warehouse, or lakehouse patterns.
• Experience with column-oriented data storage and serialization formats such as Parquet or Arrow.
• Knowledge of distributed application components including Kafka, Redis, or other messaging and caching tools.
• Proven skills in code optimization, performance tuning, and debugging across all levels of the application stack.
• Excellent communication skills to collaborate within a global team environment.