Head of Market Data

Company Description

BHFT is a proprietary algorithmic trading firm, operating across a variety of asset classes. 

Our team manages the full trading cycle, from software development to creating and coding strategies and algorithms. 

We’ve got a team of 200+ professionals, with a strong emphasis on technology—70% are technical specialists in development, infrastructure, testing, and analytics spheres. The remaining part of the team supports our business operations, such as Risks, Compliance, Legal, Operations and more.

Our employees are located all around the world, from the United States to Hong Kong. Although we maintain office spaces, we currently operate as a 100% remote organization.

Job Description

Role Overview

We are seeking a visionary and technically skilled Head of Market Data to lead the design, development, and evolution of our market data infrastructure. This individual will play a pivotal role in shaping our data architecture, ensuring the seamless acquisition, storage, and accessibility of high-quality historical market data for trading and research teams.

The ideal candidate is both a strategic leader and a hands-on expert, with deep knowledge of L1-3 exchange data and the ability to architect fast, scalable, and high-performance data solutions.

Job Description

Strategic Leadership

• Define the vision and strategy for the company’s market data systems, ensuring alignment with trading and research objectives.
• Lead, mentor, and grow a high-performing market data engineering team.

Data Platform Architecture

• Architect high-performance, scalable data platforms and lakes capable of managing large-scale historical market data, including data normalization and storage optimization.
• Develop solutions for efficient user APIs, ensuring seamless access to data for backtesting, research, and analytics.

Historical Data Management

• Oversee the design and maintenance of systems for acquiring, cleansing, and storing historical market data from exchanges, brokers, and data vendors.
• Implement robust processes for data validation, normalization, and versioning to ensure accuracy and integrity.
• Ensure the reconciliation of data changes, including handling corrections to past data and adapting to changes in exchange formats.

Collaboration and Stakeholder Engagement

• Partner closely with quantitative researchers, traders, and other stakeholders to understand data requirements and optimize systems for strategy development and backtesting.
• Establish strong relationships with market data providers, ensuring robust integrations and consistent data availability.
• Ensure market data solutions support exchange-traded options, cash equities, and futures, optimizing systems for these asset classes’ unique data requirements.

Operational Excellence

• Drive the scalability and performance of data systems to accommodate growing data volumes and evolving organizational needs.
• Optimize data storage costs while maintaining high levels of performance and reliability.
• Ensure compliance with regulatory requirements and support data retention and reporting audits.

Qualifications

Required Skills and Experience:

• Proven leadership experience in managing and developing market data systems within a financial institution, proprietary trading firm, or buy-side environment.
• Hands-on expertise with L1-3 exchange data, including addressing challenges such as cleansing and normalization.
• Strong programming skills in Python and Go, or Rust.
• Deep knowledge of market data formats (e.g., MDP, ITCH, FIX) and APIs from exchanges and data providers.
• Expertise in distributed data systems (e.g., Hadoop, Kafka, Spark) and ETL processes for handling large-scale datasets.
• Advanced proficiency in SQL, including complex queries, performance tuning, and data modeling.
• Extensive experience with Linux/Unix systems and their optimization for data storage and processing.
• Bachelor’s degree in Computer Science, Engineering, or a related field.

Preferred Qualifications:

• Experience working with unstructured datasets and alternate data sources.
• Proficiency with cloud storage platforms (e.g., AWS S3, Google Cloud Storage, Azure) and cost-performance optimization.
• Familiarity with data governance and compliance standards for financial data.
• Knowledge of containerization and orchestration tools (e.g., Docker, Airflow, SLURM).
• Exposure to machine learning workflows to support quantitative research teams.

Additional Information

What we offer:

• Working in a modern international technology company without bureaucracy, legacy systems, or technical debt.
• Excellent opportunities for professional growth and self-realization.
• We work remotely from anywhere in the world, with a flexible schedule.
• We offer compensation for health insurance, sports activities, and non-professional training.