Data Architect

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.

Requirements

• 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.
• Experience architecting and integrating Feature Stores with consistency between offline research and online trading systems.
• 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.

Preferred Qualifications

• Experience with cloud platforms (AWS, GCP, Azure) and distributed data processing frameworks (Spark, Flink, Kafka, etc.).
• Familiarity with financial data standards and protocols (FIX, XML, JSON, etc.).
• Strong knowledge of data governance, data lineage, and data quality monitoring tools.
• Experience with machine learning and data science workflows.
• Familiarity with DevOps practices and CI/CD pipelines.

Benefits

• 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.

About the Company

BHFT is a proprietary algorithmic trading firm managing the full trading lifecycle — from software development to designing and deploying trading strategies. We operate across major exchanges and a wide range of asset classes, including equities, derivatives, options, commodities, and rates, using both high-frequency (HFT) and medium-frequency (MFT) approaches.

We are a 230-person company with a strong technology focus, where 70% of the team are engineers and technical specialists. As we expand into new markets and products, we foster a results-driven culture built on innovation, collaboration, and continuous improvement, supported by a globally distributed, remote-friendly team.