Head of Market Data Development and Engineering, Galaxy

• 10+ years of experience in custom development of real time market data platforms within a trading firm, hedge fund, or financial institution
• Knowledge of key market data vendors, exchanges, and licensing models
• Strong understanding of trading workflows, asset classes (equities, futures, options, FX, fixed income), and data types (real-time, reference, historical)
• Experience with low-latency data systems, market data feeds, APIs, and streaming technologies
• Strong analytical and problem-solving skills with attention to detail
• Excellent communication skills, with the ability to engage both technical and business stakeholders

Desirable

• We are seeking an experienced Head of Market Data Development and Engineering to lead the development, delivery, acquisition, governance, and optimization of market data for both digital and traditional assets across the firm
• This role sits at the intersection of trading and technology ensuring high-quality, cost-effective, performant, and compliant data services that power trading, research, and risk systems
• You’ll work closely with trading teams, stakeholders, and external partners to deliver critical initiatives that drive our business forward. If you’re a natural problem-solver with a passion for hands-on technical development in a global, fast-paced environment, we want to hear from you
• Market Data Strategy & Architecture
• Define and execute a unified market data strategy across centralized crypto exchanges (CEX), decentralized venues (DEX), and traditional markets
• Design scalable, low-latency data architecture supporting tick-level, order book, and on-chain data
• Evaluate build vs. buy decisions for internal data platforms vs. external providers
• Development Manager and hands on Development
• Lead a small team of developers and be hands on yourself
• Design and build a Market Data API to front all data sources including custom feedhandlers, vendor platforms, Kdb+, and DataBricks
• Manage the Market data messaging bus used by all internal applications in the firm
• Crypto Market Data & Vendor Management
• Build relationships with crypto exchanges (e.g., Binance, Coinbase, Deribit, OKX), data aggregators, and node providers
• Assist our vendor management team with commercial negotiations, licensing, and exchange agreements across both crypto and traditional markets
• Data Quality, Normalization & Coverage
• Ensure high-quality, normalized datasets across fragmented crypto venues (symbol mapping, schema standardization, latency benchmarking)
• Oversee ingestion of real-time order book data, trades, reference data, funding rates, and on-chain metrics
• Establish monitoring and alerting frameworks for data integrity and completeness
• Cost Management & Optimization
• Manage and optimize the global market data budget across crypto and traditional vendors
• Identify cost-saving opportunities through vendor consolidation, direct exchange connectivity, and internal data solutions
• Implement usage tracking and chargeback models where appropriate
• Infrastructure Partnership
• Partner with infrastructure teams to build the pipes necessary to bring in market data
• Support hybrid environments (on-prem + cloud) and ensure resilience, redundancy, and scalability
• Enable data access for research, backtesting, and production trading systems
• Regulatory & Compliance Oversight
• Ensure compliance with exchange licensing, redistribution rules, and evolving crypto regulatory frameworks
• Implement entitlement controls, audit trails, and governance policies across all data usage
• Stakeholder Collaboration
• Work closely with trading, quant research, risk, and portfolio management teams to deliver data solutions
• Support onboarding of new exchanges, instruments (perpetuals, options), and strategies
• Act as the firm’s subject matter expert on both crypto and cross-asset market data
• Leadership & Team Development
• Build and lead a high-performing development team
• Establish best practices for market data onboarding, validation, and lifecycle management
• Foster a culture of innovation, automation, and operational excellence
• Embrace and champion the thoughtful adoption of AI to improve team performance and business outcomes
• Leverage AI tools (e.g., generative AI, automation platforms, data copilots) to improve productivity, decision-making, and output quality in your day-to-day work