Data Architect
This role sits at the core of our trading infrastructure. As a Data Architect, you will design scalable, low-latency, and highly reliable data systems that support both live trading and large-scale research. You will own the architectural vision for the Market Data Lakehouse, ensuring that all components built by the data engineering team integrate into a cohesive, efficient, and production-grade environment.
The position requires strong technical leadership and a deep understanding of financial market data, including its structure, quality challenges, and performance requirements. You will work closely with researchers, trading teams, and engineers, enabling fast experimentation while maintaining strict reliability, governance, and operational standards.
This is a high-impact role with significant ownership and influence over BHFT’s trading technology stack.
Key Responsibilities
Architect and standardize streaming and batch pipelines, ensuring reliability, fault tolerance, and scalability.
Own the architecture and evolution of the Data Lakehouse, ensuring consistency between research (offline) and live trading (online) environments.
Define and own the end-to-end architecture for the market data platform, covering ingestion, processing, storage, distribution, and access.
Design scalable, low-latency systems for real-time and historical market data across multiple global exchanges and asset classes.
Establish data models, schemas, storage strategies, and technology choices optimized for high-volume time-series financial data.
Provide architectural leadership across the full development lifecycle, including design reviews, standards, and technical integration of team deliverables.
Collaborate closely with quantitative researchers, trading, and engineering teams to enable fast experimentation and reliable production deployment.
Drive performance optimization, capacity planning, and long-term scalability of the data ecosystem.
Document architectural decisions and maintain technical roadmaps to ensure high engineering standards and platform consistency.
Qualifications
Deep understanding of market data (tick, order book, trades, reference, derivatives) and its use in HFT/MFT and systematic trading environments.
Strong financial markets background to make informed architectural decisions on storage engines, schemas, and latency trade-offs.
Proven expertise in distributed data systems (streaming, batch, and hybrid architectures) and scalable storage formats.
Experience designing and operating low-latency, production-critical data pipelines with strict SLAs.
Advanced data modeling skills, particularly for large-scale time-series financial datasets.
End-to-end architectural vision across ingestion, processing, storage, serving, and feature computation layers.
Design and build pipelines, storage platforms, and tooling to centralize machine learning feature engineering, ensuring consistency between offline research and real-time trading systems while operating at scale on large datasets.
Strong ownership of data quality, governance, monitoring, lineage, and observability frameworks.
Ability to evaluate trade-offs (latency vs cost, flexibility vs performance, consistency vs availability) and make structured architectural decisions.
Technical leadership capability: setting standards, reviewing designs, mentoring engineers, and ensuring cohesive integration across teams.
Additional Information
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, professional training, and more.