Senior Data Architect (USA)

Responsibilities

• Architect and implement a unified data platform that integrates hundreds of vendor datasets, providing consistent, accessible, and high-quality data to simulators and researchers.
• Design efficient storage and retrieval systems to support both large-scale historical backtesting and high-frequency research workflows.
• Develop intuitive researcher interfaces and APIs that allow users to easily discover variables, explore metadata, and assemble data into standardized stocks × values matrices for rapid hypothesis testing.
• Collaborate closely with quantitative researchers and simulation teams to understand their workflows, ensuring the data platform meets real-world analytical and performance needs.
• Establish best practices for data modeling, normalization, versioning, and quality control across asset classes and data vendors.
• Work with infrastructure and DevOps teams to optimize data pipelines, caching, and distributed storage for scalability and reliability.
• Prototype and deploy internal data applications that enhance research productivity and data transparency.
• Mentor and guide data engineers to maintain robust, maintainable, and well-documented data systems.

Requirements

• 7+ years of experience in data architecture, quantitative research infrastructure, or large-scale data engineering in a financial or research-driven environment.
• Proven experience designing and implementing scalable data storage solutions (e.g., columnar databases, time-series systems, object stores, or data lakes).
• Strong proficiency in Python and familiarity with modern data stack technologies (e.g., Parquet, Arrow, Spark, SQL/NoSQL, distributed file systems).
• Deep understanding of time-series and financial data modeling, including handling multiple vendors, instruments, and frequencies.
• Experience building data interfaces, APIs, or tools that serve researchers, data scientists, or quantitative analysts.
• Ability to translate research needs into efficient data schemas and access patterns.
• Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Mathematics, or a related quantitative field.
• Strong collaboration, communication, and documentation skills.

Nice-to-Haves

• Familiarity with cloud-based architectures (e.g., AWS, GCP, Azure) and modern data governance practices.

Compensation & Benefits

• Base salary range: $175,000 - $200,000 depending on candidate’s background.
• Bonus based on individual and company performance.
• PPO health, dental, and vision insurance premiums fully covered.
• Pre-tax commuter benefits.
• Weekly company meals.