BHFT
Financial Services
MarketDataEngineer(DomainTradingExpertiseRequired)
Neural analysis suggests this role is
optimal for mid candidates.
“Market Data Engineer (Domain Trading Expertise Required) at BHFT. Skills: Market Data Engineering, Lakehouse architecture, Apache Iceberg, Python. Capture exchange feeds. Ingest vendor sources”
Industry & Context.
Gap handling; Troubleshooting
What They're Looking For.
Must Have
5+ years building data systems, Architecting data lakes from scratch, Launching data lakes from scratch, Apache Iceberg experience, Market data experience, Network packet capture experience, Exchange feed protocols experience, Order-book reconstruction experience, Time-series at scale experience, Expert-level Python, Modern orchestration experience, Distributed processing experience, Advanced SQL, Linux fundamentals, Containerization fundamentals, Cloud object storage fundamentals, DevOps fundamentals, Observability fundamentals, CI/CD experience, Infrastructure-as-code experience, GitOps experience, Metrics/dashboards/alerting experience, Structured data grasp, Unstructured data grasp, Binary data grasp, Storage optimization grasp, English fluency
Nice to Have
Comparable table formats experience, Apache Arrow familiarity, Rust proficiency, Market data normalization experience, Unified schema normalization experience, Symbology normalization experience
What You'll Do.
Capture exchange feeds
Ingest vendor sources
Build batch pipelines
Build stream pipelines
Reconstruct L2/L3 order-book
Handle order-book gaps
Provide Python producer SDKs
Provide Rust producer SDKs
Design Iceberg partitioning
Design Iceberg sort orders
Design Iceberg row-group layout
Manage Iceberg schema evolution
Manage Iceberg snapshots
Manage Iceberg time travel
Manage Iceberg compaction
Maintain reference data tables
Drive storage cost optimisation
Build schema management libraries
Build data contract libraries
Build data validation libraries
Build data lineage libraries
Develop shared access services
Own data-quality dashboards
Own incident runbooks
Partner with Quant Research
Partner with Data Science
Translate requirements
Champion best practices
How You'll Work.
Team & Collaboration
Quant Research; Data Science; Backend; DevOps
Process & Methodology
CI/CD, GitOps
Full Job Description
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- and Medium-Frequency Trading approaches. We’re 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. The Data Engineering team is responsible for designing, building, and maintaining the Market Data Platform — a lakehouse infrastructure spanning the full path from raw exchange feeds to reliable, petabyte-scale data for research, backtesting, and real-time trading. Key Responsibilities * Capture & Ingestion. Own the full capture path from wire to lake: decode and normalize raw exchange feeds (pcap, multicast UDP / ITCH / FIX) and vendor sources (OneTick, Refinitiv, Bloomberg, ICE) into a unified canonical model with nanosecond timestamps. Build batch + stream pipelines (Airflow, Spark, dbt) for tick and reference data. Own L2/L3 order-book reconstruction with gap handling. Provide Python and Rust producer SDKs for internal feed handlers. * Storage & Modeling — Apache Iceberg. Own the Iceberg-over-S3 lakehouse: design partitioning, sort orders, and row-group layout for fast scans; manage schema evolution
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