Data Engineer

We are looking for a highly motivated Data Engineer to join a small and growing team at a high-performing trading firm. This role is ideal for those who want to see tangible impact from their work. You will be collaborating directly with quants and portfolio managers to architect data flows and build resilient ETL systems that power real-time decision-making.

This is not a back-office or purely maintenance role. You will help shape how the firm ingests, processes, and leverages data across multiple strategies. The position offers significant ownership and influence for engineers who enjoy seeing the direct results of their technical contributions. This is a rare opportunity.

We are especially interested in candidates who prefer working on-premises infrastructure, value clarity and performance in their code, and have strong instincts around data reliability and system orchestration.

• Python
• SQL
• Airflow
• Unix/Linux
• Postgres
• MongoDB
• on‑premises infrastructure
• Git
• data warehousing
• data modelling

Austin, TXor Chicago, IL(hybrid format, with a requirement of 3 days per week in the office).

• Competitive, market‑leading compensation package (aligned with top‑tier trading firms);
• Private health, vision, and dental insurance;
• Flexible paid sick leave;
• Impact‑driven environment where contributions are visible and valued;
• The opportunity to work closely with PMs, quants, and senior engineering leadership;
• High level of ownership and the ability to directly influence data architecture and strategy.

• Strong knowledge of Python and SQL;
• Experience with on‑premises data infrastructure (e.g., Hadoop);
• Familiarity with cloud platforms, e.g. AWS or GCP;
• Hands‑on experience with Airflow (or similar orchestration tools);
• Proficiency with Unix/Linux systems;
• Familiarity with relational and No
  
  SQL databases (Postgres, Mongo
  
  DB, etc.);
• Understanding of data modelling principles and trade‑offs (normalisation vs denormalisation);
• Comfortable with Git workflows and collaborative engineering environments;
• Bachelor's degree in Computer Science, Engineering, or related technical field.

• Partner with PMs and Quant Developers to translate trading and research needs into reliable data pipelines;
• Expand and maintain the internal data warehouse;
• Build and optimise ETL workflows using orchestration tools (Airflow preferred);
• Improve robustness, speed, and scalability of internal data tools;
• Implement monitoring, anomaly detection, and data quality checks;
• Manage data entitlements and vendor relationships;
• Evaluate and propose tooling for data ingestion, streaming, and management.

• Experience working in fast‑paced tech or financial environments;
• Background in data engineering for trading or analytics products;
• Java skills are a bonus;
• Master's degree in a quantitative or technical field.

If this sounds like the kind of environment where you do your best work, we would love to meet you.