Software Engineer, Data Platform

About the role

Our systems operate at the massive speed and scale of algorithmic trading. We process terabytes of data and billions of rows each day, and every layer of the platform must be engineered for performance and reliability. As a small team, we are continuously evolving our analytics platform to keep pace with growing datasets and increasingly complex analytical workloads.

We are seeking a software engineer who enjoys building the systems that make large-scale data usable. This role sits at the intersection of data engineering and backend development, focused on building and improving the infrastructure that powers our analytics platform. That includes designing data pipelines, workflow orchestration, and internal tooling that supports high-volume, time-sensitive data processing.

The ideal candidate is comfortable working with both real-time and historical data streams and has experience managing end-to-end data workflows. You will help design and maintain the services, pipelines, and platform infrastructure that support our analytics initiatives, working closely with both engineering and the business to turn complex datasets into usable systems.

This role is based in one of our offices in New York, London, or Amsterdam, with hybrid flexibility.

What You’ll Do

- Work with engineers and business teams to understand our datasets and build systems to store, process, and productionize them.

- Develop and maintain reliable data pipelines and workflow systems for large-scale data ingestion and transformation.

- Build internal services and tooling that support analytics, automation, and data operations.

- Implement ETL and data transformation processes for analytical databases and internal applications.

- Develop and maintain workflow orchestration for complex data processes.

- Optimize storage, retrieval, and processing performance across large datasets.

- Partner with analysts and researchers to support data modeling and analytics workflows.

- Monitor and troubleshoot data infrastructure to ensure reliability and data integrity.

- Continuously improve the platform through better system design, tooling, and engineering practices.

Who You Are

- You have a Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent hands-on experience.

- You bring around 3-5 years of experience building internal data platform tooling or services that support large-scale data processing and analytics workflows (primarily using Python and SQL; Rust is a plus).

- You’ve worked with workflow orchestration systems used to manage complex data pipelines (Temporal, Airflow, Dagster, or similar).

- You’re familiar with columnar data formats such as Parquet or Arrow.

- You have experience working with large-scale datasets and high-volume data pipelines in production environments.

- Experience working with analytics platforms, data providers, or financial data systems is a plus.