BHFT is a proprietary algorithmic trading firm. Our team manages the full trading cycle, from software development to creating and coding strategies and algorithms.
Our trading operations cover key exchanges. The firm trades across a broad range of asset classes, including equities, equity derivatives, options, commodity futures, rates futures, etc. We employ a diverse and growing array of algorithmic trading strategies, utilizing both High-Frequency Trading (HFT) and Medium-Frequency Trading (MFT) approaches.
Looking ahead, we are expanding into new markets and products. As a dynamic company, we continuously experiment with new markets, tools, and technologies.
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.
With a strong focus on innovation and performance, BHFT is actively expanding its presence in traditional financial markets. We value a results-driven culture, emphasizing collaboration, transparency, and constant improvement, all while offering the flexibility of remote work and a globally distributed team.
Job DescriptionWe are building a world-class data platform to support systematic trading across 10+ global exchanges. This role will lead the Data Engineering team responsible for ingesting, processing, storing, and serving all market, reference, and alternative data with low latency and high reliability. You will also own the architecture and evolution of our Feature Store, which powers our live trading systems and research pipeline.
This is a hands-on technical leadership position with significant ownership and influence over our trading technology stack.
Key Responsibilities
You’ll drive end-to-end delivery of key data engineering projects, such as:
A unified platform for collecting and serving market data.
Real-time and batch pipelines that transform raw data into usable features.
A central store for offline, online, and streaming features.
Frameworks to ensure data quality, consistency, and reliability.
Tools for managing historical datasets and replaying data for research.
Scalable storage and processing systems used by researchers and production systems.
Lead & Deliver
Grow and mentor a Data Engineering team.
Translate business and research needs into clear plans and roadmaps.
Set engineering standards around code quality, testing, and CI/CD.
Drive execution of the team’s long-term data platform strategy.
Own Data Engineering
Oversee ingestion and processing of live and historical datasets.
Define SLAs, data quality metrics, and monitoring.
Manage schemas, storage formats, and dataset governance.
Standardize data representations across different sources.
Feature Platform Ownership
Design architectures for generating and serving features.
Maintain low-latency pipelines used in production systems.
Oversee intra-day feature computation and transformations.
Ensure reproducibility, versioning, and lineage across the feature stack.
Infrastructure & Tooling
Build and maintain data collectors and ingestion services.
Manage scalable storage solutions for research and production use.
Own metadata and cataloging tools.
Develop compute workflows for feature updates and model support.
Collaboration
Work closely with researchers to enable fast experimentation.
Partner with engineering teams to ensure smooth integration into production systems.
Collaborate with compliance and risk functions on governance and auditability.
6+ years in Data Engineering, with at least 2+ years in a lead role.
Prior experience in trading, HFT, systematic hedge fund, crypto exchange, or similar.
Profound expertise in diverse types of market data.
Deep expertise in:
Streaming systems (Kafka, Redpanda, Pulsar, Kinesis, or equivalent)
Columnar storage (Parquet, ORC)
Distributed compute (Spark, Flink, Ray, Dask)
Python + one of: Rust / Go / C++
Proven ownership of data pipelines supporting latency-sensitive environments.
Strong ownership mentality and ability to work independently.
Ability to break down ambiguous problems into clear deliverables.
Excellent written and verbal communication.
Leadership mindset: developing engineers, setting standards, documenting decisions.
Would be a plus
Built a Feature Store.
Experience supporting quant researchers (alphas, signals, features).
Time-series databases.
Managed onboarding of multiple exchanges or large-scale datasets.
Comprehensive awareness of common challenges associated with various market data vendors, data types, and formats.
Demonstrated experience in managing exchange-specific intricacies, data entitlements, and data quality issues.
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 professional training.
