Job responsibilities

• Represents the data architecture team at technical governance bodies, providing feedback and proposing improvements to data architecture governance practices and guiding evaluation of current and new technology using existing data architecture standards and frameworks
• Uses enterprise-authorized AI capabilities within the work environment to accelerate data architecture analysis and decisioning (e.g., option evaluation and documentation), validating outputs and handling data according to sensitivity and security requirements
• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors and serves as a function-wide subject matter expert in one or more areas of focus
• Develops secure and high-quality production code and reviews and debugs code written by others
• Drives data architecture decisions that impact product design, application functionality and technical operations and processes
• Actively contributes to the engineering community as an advocate of firmwide data frameworks, tools, and practices in the Software Development Life Cycle
• Influences peers and project decision-makers to consider the use and application of leading-edge technologies
• Leads reuse-first adoption of AI-assisted data validation within SDLC/toolchain routines, improving quality checks and operational stability with traceability/auditability and resiliency expectations
• Experience defining enterprise Data + Agentic AI platform and reference architecture spanning ingestion, curated data products, metadata/lineage, enterprise knowledge bases (vector search/RAG), agent toolchains (planning/execution), guardrails, access controls/risk controls, and evaluation/observability
• Guides the implementation of enterprise data solutions, ensuring alignment with business goals and compliance requirements
• Collaborates with cross-functional teams to drive innovation and continuous improvement in data architecture

Required qualifications, capabilities, and skills

• Formal training or certification on data architecture concepts and 5+ years applied experience
• Hands-on practical experience delivering system design, application development, testing, and operational stability
• Demonstrated experience using enterprise-authorized AI capabilities within the work environment to support data architecture workflows with strong validation habits and awareness of data sensitivity
• Ability to assess and validate AI-assisted data architecture recommendations before adoption, escalating uncertainty and ensuring outcomes align to resiliency, security, and auditability expectations
• Advanced in one or more programming language(s), applications, and architecture, with advanced knowledge of architecture, applications, and technical processes within one or more technical disciplines (e.g., Cloud, AI/ML, mobile, etc.)
• Ability to tackle design and functionality problems independently with little to no oversight
• Ability to evaluate current and emerging technologies to select or recommend the best solutions for the future state architecture
• Experience defining enterprise Data + Agentic AI platform and reference architecture spanning ingestion, curated data products, metadata/lineage, enterprise knowledge bases (vector search/RAG), agent toolchains (planning/execution), guardrails, access controls/risk controls, and evaluation/observability
• Strong communication and collaboration skills to work effectively with cross-functional teams
• Proven track record of delivering high-quality data architecture solutions in complex environments
• Familiarity with data governance, security, and compliance standards
   

• Experience in financial services or regulated industries
• Master’s degree in a relevant field
• Familiarity with data governance, security, and compliance standards
• Experience with agile methodologies
• Certification in cloud or data architecture
• Knowledge of machine learning and advanced analytics

• Published work or presentations in data architecture