Architect Jobs

About The Position

Requirements

• 10-12+ years of experience in data engineering, data architecture, or related fields
• Proven experience evaluating and re-architecting data platforms at scale
• Strong hands-on experience building distributed data pipelines and systems
• Deep expertise in AWS-based data architecture
• Strong programming and data engineering skills, including Python, SQL, workflow orchestration tools (e.g., Airflow), and ETL/ELT frameworks
• Extensive experience in database design and data modeling, including time-series and financial data, normalized and denormalized schemas, and relational and columnar databases
• Experience with caching technologies (e.g., Redis) and performance optimization
• Solid understanding of financial markets and asset classes, including fixed income, commodities, equities and derivatives, and digital assets
• Experience leading engineering teams and driving architectural decisions
• Strong familiarity with market data vendors such as Bloomberg, LSEG, and ICE
• Applicants must be authorized to work in the U.S. without the need for employer-sponsored work authorization, now or in the future.

Nice To Haves

• Experience in a multi-strategy hedge fund, asset manager, or leading market data provider (e.g., Bloomberg, LSEG, ICE Data Services)
• Familiarity with real-time and streaming architectures (e.g., Kafka, Kinesis)
• Experience with data governance, lineage, and data quality frameworks
• Experience building canonical data platforms or enterprise data layers

Responsibilities

• Assess the current market data architecture, identify gaps, and define a target-state architecture in collaboration with the Director of Research & Investment Technology
• Lead the design and implementation of a scalable, resilient, and extensible data platform
• Establish architectural principles, standards, and best practices across data engineering
• Drive re-architecture initiatives to improve performance, scalability, and maintainability
• Lead evaluation and selection of core data platform tools and frameworks, including ETL/ELT pipelines, workflow orchestration (e.g., Airflow), data storage (lakes, warehouses), and caching layers (e.g., Redis)
• Make build vs. buy decisions and define the long-term data technology stack
• Standardize tooling and promote engineering best practices across the team
• Architect and build robust ETL/ELT pipelines for ingesting and processing data from multiple vendors (e.g., Bloomberg, LSEG, ICE, etc.)
• Design workflows for data normalization, symbology mapping, enrichment, and distribution
• Implement monitoring, alerting, and failure recovery mechanisms
• Work hands-on with large-scale financial datasets
• Lead the design of scalable data models for market and reference data
• Define canonical data models and schema standards across asset classes
• Optimize database design for performance, flexibility, and analytical use cases
• Design systems to handle vendor-specific schemas, symbology mapping, and entitlements
• Design and implement caching strategies (e.g., Redis) to support low-latency data access
• Optimize data access patterns and overall system performance
• Balance real-time and batch processing requirements
• Partner with DevOps to design and manage cloud-native data platforms using AWS services (e.g., S3, Lambda, Glue, EMR, Redshift, ECS/EKS)
• Optimize infrastructure for cost, performance, and scalability
• Lead and mentor a team of data engineers, setting technical direction and standards
• Guide the team on tool selection, architectural decisions, and implementation approaches
• Conduct code and design reviews with a focus on scalability and maintainability
• Foster a culture of ownership and engineering excellence

Benefits

• medical, dental and vision coverage
• telemedicine services
• life, accident and disability insurance
• parental leave and family planning benefits
• caregiving resources
• a generous retirement program
• financial guidance
• paid time off
• bonuses