Senior Data Architect

Role Overview

This key hire is driven by the need to enhance and unify research and simulation data ecosystems. The Senior Data Architect will play a critical role in designing the future of the data infrastructure, providing the backbone for groundbreaking research, sophisticated simulations, and alpha generation across diverse asset classes. This position offers an exceptional opportunity to shape strategic data architecture that will directly influence the organization's success and innovation trajectory.

• Lead the design and implementation of a comprehensive, scalable data platform integrating hundreds of datasets from multiple vendors.
• Develop systems for efficient storage, retrieval, and real-time access to complex financial data, supporting both historic backtesting and high-frequency research workflows.
• Create user-friendly interfaces and APIs enabling researchers to discover, explore, and utilize data effectively.
• Collaborate with research and engineering teams to understand their operational needs, translating these into optimized data models and schemas.
• Establish best practices for data quality, normalization, version control, and compliance across various asset types.
• Partner with infrastructure teams to enhance scalability, reliability, and performance through optimized pipelines and distributed storage.
• Prototype and deploy internal tools to improve research productivity, transparency, and data governance.
• Mentor and guide data engineering colleagues to promote best practices in data architecture and documentation.

• 7+ years' experience in data architecture, large-scale data engineering, or research infrastructure within financial or similar environments.
• Proven expertise in designing scalable storage solutions such as data lakes, time-series databases, or columnar systems.
• Strong proficiency in Python and familiarity with modern data technologies including Parquet, Spark, SQL/No
  
  SQL, and distributed file systems.
• In-depth knowledge of financial data modelling, particularly handling multi-vendor, multi-instrument datasets across various frequencies.
• Experience developing data interfaces, APIs, or tools tailored for researchers, data scientists, or quantitative analysts.
• A degree in Computer Science, Engineering, Mathematics, or a related field; advanced qualifications are advantageous.
• Excellent teamwork, communication, and documentation skills.
• Familiarity with cloud platforms such as AWS, GCP, or Azure and contemporary data governance practices is beneficial.
• Experience working with cloud-based architectures and modern data governance standards.
• Knowledge of financial markets, instruments, and trading data workflows.
• Prior involvement in mentoring or leading data engineering teams.

This role is based in either NYC or CT, applicants will be required to be in office at either location.