JPMorgan Senior Lead Data Architect-Vice President 

United States, New Jersey, Jersey City 

21209188

Job responsibilities

• Represents the data architecture team at technical governance bodies and provides feedback regarding proposed improvements regarding data architecture governance practices
• Evaluates new and current technologies using existing data architecture standards and frameworks
• Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors
• Design secure, high-quality, scalable solutions and reviews architecture solutions designed by others
• Drives data architecture decisions that impact data product & platform design, application functionality, and technical operations and processes
• Serves as a function-wide subject matter expert in one or more areas of focus
• Actively contributes to the data 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
• Advises junior architects and technologists

Required qualifications, capabilities, and skills

• 7+ years of hands-on practical experience delivering data architecture and system designs, data engineer, testing, and operational stability
• Advanced knowledge of architecture, applications, and technical processes with considerable in-depth knowledge in data architecture discipline and solutions (e.g., data modeling, native cloud data services, business intelligence, artificial intelligence, machine learning, data domain driven design, etc.)
• Practical cloud based data architecture and deployment experience, preferably AWS
• Practical SQL development experiences in cloud native relational databases, e.g. Snowflake, Athena, Postgres
• Ability to deliver various types of data models with multiple deployment targets, e.g. conceptual, logical and physical data models deployed as an operational vs. analytical data stores
• Advanced in one or more data engineering disciplines, e.g. streaming, ELT, event processing
• 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 data architecture

Preferred qualifications, capabilities, and skills

• Financial services experience, card and banking a big plus
• Practical experience in modern data processing technologies, e.g., Kafka streaming, DBT, Spark, Airflow, etc.
• Practical experience in data mesh and/or data lake
• Practical experience in machine learning/AI with Python development a big plus
• Practical experience in graph and semantic technologies, e.g. RDF, LPG, Neo4j, Gremlin
• Knowledge of architecture assessments frameworks, e.g. Architecture Trade off Analysis