BHFT

Financial Services

MarketDataEngineer

₹25–45L ~AI est. Barcelona, CT, Spain FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for mid candidates.

The Brief

“Market Data Engineer at BHFT. Skills: Market Data Engineering, Lakehouse architecture, Apache Iceberg, Python. Capture exchange feeds. Ingest vendor sources”

Industry & Context.

Financial Services
Problems you'll solve

Gap handling; Gap detection; Pcap reconciliation; 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, Delta Lake experience, Hudi experience, Market data experience, Network packet capture experience, Decode pcap 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 fundamentals, Infrastructure-as-code fundamentals, GitOps fundamentals, Metrics/dashboards/alerting fundamentals, Structured data grasp, Unstructured data grasp, Binary data grasp, Storage optimization grasp, English fluency

Nice to Have

Normalize market data experience, Rust proficiency, Kubernetes experience

What You'll Do.

Capture exchange feeds

Ingest vendor sources

Build batch pipelines

Build stream pipelines

Reconstruct order-books

Handle order-book gaps

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

Optimize storage costs

Build schema libraries

Build data contract libraries

Build data validation libraries

Build data lineage libraries

Develop shared access services

Reconcile pcap vs lake

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 teams; DevOps teams; Cross-functional teams

Communication Scope

Documentation; Collaboration

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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