Job
Description
As a Senior Lead Data Architect at JPMorgan Chase within the Consumer and Community Banking Data Technology, you are an integral part of a team that works to develop high-quality data architecture solutions for various software applications, platform and data products. Drive significant business impact and help shape the global target state architecture through your capabilities in multiple data architecture domains. 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 Formal training or certification on software engineering concepts and 5+ years of applied experience 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
