Data Engineer

Introduction

Boothbay Fund Management, LLC is a multi-manager, multi-strategy firm with 100+ alternative asset managers trading strategies across a spectrum of asset classes globally. Boothbay launched its flagship strategy in 2014. Boothbay has its primary office in NYC, and additional offices in London, Hong Kong, and Westchester. The firm is operated with an entrepreneurial spirit and is continually seeking to improve and expand.

Role

We are seeking a talented Data Engineer to join the growing data team within our Quantitative Management Division This position is ideal for individuals who are passionate about building scalable data solutions, eager to learn in a collaborative environment, and excited to work in small teams while taking advantage of opportunities to lead and enhance both themselves and their teammates.

In this role, you will collaborate with experienced engineers to build and maintain our data infrastructure, develop efficient data pipelines, and ensure data quality across our systems. As part of a small team in the early stages of its lifecycle, you will have significant opportunities to make a meaningful impact and contribute to shaping our processes and systems.

Key Responsibilities

• Contribute components of our mission critical data platform for the purposes of live trading and strategy research.
• Collaborate with researchers to optimize data delivery.
• Make available new datasets
• Implement data quality checks and monitoring systems.
• Assist in database design and optimization.
• Write clean, maintainable code following best practices.
• Participate in code reviews and documentation.

Qualifications

• A degree in Computer Science, Mathematics, Physics or other quantitative discipline. Postgraduate an advantage.
• Experience with financial data sets
• Very strong Python, with emphasis on data engineering and systems programming.
• Good understanding of ETL processes, databases and other data management tools such as data lakes and DBT.
• Some exposure to DB Engine operation. Clustering, performance tuning, backups.
• Linux/Unix
• Excellent problem-solving and analytical skills.
• Strong communication, and collaboration abilities.

Preferred Qualifications

• Experience with columnar DB engines like Clikchouse, KDB/Q or similar
• Experience with Airflow, Dagster or similar tools.
• Exposure to container technologies: Docker, Podman etc
• Knowledge of 'big data' technologies (Hadoop, Spark, Parquet)
• Experience with TAQ data, and exchange connectivity.

Compensation

• Anticipated Salary Range for United States: $100,000 - $150,000 base salary, plus eligible for discretionary bonus commensurate with performance

Primary work location

• London, NYC or Westchester (Hybrid)