Data Infrastructure Architect

Data Architect - Quantitative Trading Overview We are seeking an experienced Data Architect to design and manage mission-critical on-premise data infrastructure for our quantitative trading operations. This role sits at the intersection of high-performance systems design and financial data architecture, requiring deep expertise in building low-latency, scalable systems that support real-time algorithmic trading strategies.

Core Responsibilities Infrastructure & Architecture Design Design and architect on-premise data infrastructure optimized for real-time market data ingestion, processing, and analysis Develop comprehensive data models, schemas, and physical database designs supporting microsecond-level latency requirements Lead system design decisions for mission-critical components handling high-frequency trading data Create detailed architecture documentation and design specifications for trading data systems Establish data standards, best practices, and architectural patterns across engineering teams Performance & Optimization Optimize database performance for real-time queries on massive tick data and market microstructure datasets Conduct performance tuning of SQL queries, indexing strategies, and data access patterns Manage storage optimization and implement efficient data compression techniques for on-premise systems Monitor system metrics and implement continuous performance improvements Design and implement caching strategies and buffer management for low-latency access Data Pipeline & ETL Management Architect robust ETL/data pipeline solutions for real-time and batch data ingestion Design fault-tolerant systems for continuous market data feeds with guaranteed delivery Manage data quality, validation, and transformation at scale Oversee integration between trading systems, data warehouses, and analytics platforms Implement disaster recovery and business continuity strategies for on-premise infrastructure System Reliability & Operations Ensure data security, integrity, and compliance with regulatory requirements Manage backup, recovery, and migration strategies Collaborate with trading teams to understand low-latency requirements and system constraints Participate in capacity planning and infrastructure provisioning decisions Lead troubleshooting of complex data-related issues in production trading systems GPU & Accelerator Infrastructure Management Design and architect large-scale GPU/SPU cluster infrastructure for quantitative model training and inference Manage GPU resource allocation, scheduling, and optimization across multiple workloads Oversee GPU memory management and implement efficient data movement strategies between CPU and GPU Design distributed training pipelines leveraging GPU acceleration for machine learning models Implement monitoring, performance profiling, and optimization for GPU-intensive workloads Manage high-performance interconnects and network topology for GPU clusters Plan GPU capacity planning and procurement strategies aligned with trading model requirements Troubleshoot performance bottlenecks in GPU computing pipelines

Required Technical Skills Programming & Systems Development Expert-level C++ proficiency for systems programming, data structure optimization, and performance-critical components Strong Python/Java skills for system design, prototyping, and ETL logic Deep understanding of operating systems, memory management, and process optimization Experience with multithreading, concurrency control, and synchronization primitives Ability to write efficient, maintainable code for high-performance systems Database & Data Technologies Advanced expertise in relational database systems (SQL Server, Oracle, PostgreSQL) Proficiency in physical database design, indexing strategies, and query optimization Strong SQL knowledge including window functions, CTEs, and complex query patterns Experience with NoSQL databases for specific use cases (Redis, HBase, or similar) Familiarity with in-memory databases for low-latency requirements System Design & Architecture Proven expertise in distributed systems design and implementation Strong understanding of system design principles: scalability, availability, consistency, partitioning Experience designing high-throughput, low-latency systems handling real-time data Knowledge of message queues and streaming technologies (Kafka, RabbitMQ, or equivalent) Familiarity with networking concepts and optimization (TCP/IP, socket programming) On-Premise Infrastructure Expert knowledge of Linux/Unix systems administration and optimization Experience with storage systems, RAID configurations, and SAN/NAS management Understanding of virtualization technologies and containerization where applicable Knowledge of backup, replication, and disaster recovery solutions for on-premise environments Experience with monitoring, logging, and observability tools in production systems GPU & Specialized Processor Infrastructure Proven expertise designing and managing large-scale GPU clusters (NVIDIA, AMD) for data processing and machine learning Experience with GPU memory management, CUDA/GPU computing frameworks, and GPU workload optimization Knowledge of TPU (Tensor Processing Units) and SPU (Systolic Processing Units) architecture and deployment Proficiency in distributed GPU training and inference infrastructure Experience with GPU virtualization, scheduling, and resource allocation systems Understanding of high-bandwidth interconnects for GPU clusters (InfiniBand, NVLink) Familiarity with specialized accelerator management tools and frameworks Financial Markets & Trading Systems Understanding of market data types (tick data, OHLC bars, order book microstructure) Familiarity with trading system architecture and data flow Knowledge of financial compliance and regulatory data retention requirements Experience with latency profiling and optimization for trading applications

Required Experience 5+ years of data architecture or systems engineering experience 3+ years designing and building on-premise, high-performance data systems 5+ years of professional C++ development experience 3+ years of hands-on system design and architecture work 3+ years managing large-scale GPU/SPU infrastructure and distributed GPU clusters Demonstrated track record building low-latency systems handling real-time data at scale Previous experience in quantitative trading, hedge funds, or high-frequency trading firms (preferred) Experience managing complex infrastructure projects from design through deployment

Education & Qualifications Bachelor's degree in Computer Science, Computer Engineering, Mathematics, or related quantitative field Master's degree in Computer Science, Software Engineering, or related field (preferred) Advanced certifications in database technologies or systems architecture (preferred)

Soft Skills Strong communication ability to translate between technical teams and trading operations Collaborative mindset with experience working across engineering, research, and trading teams Problem-solving approach with attention to detail and system reliability Leadership capability to mentor junior engineers and establish technical best practices Ability to balance competing priorities: performance, reliability, scalability, and maintainability

Work Environment This role involves working directly with quantitative researchers, traders, data engineers, and platform teams. You'll participate in design reviews, architecture discussions, and production troubleshooting. The position requires both strategic thinking for long-term infrastructure planning and hands-on technical work for implementation and optimization.