Description As a Lead Architect at JPMorgan Chase within the Corporate Investment Bank Information Architecture team, you are an integral part of a team that works to develop high-quality architecture solutions for various software applications and platforms products. You drive significant business impact and help shape the target state architecture through your capabilities in multiple architecture domains. You will play a crucial role in delivering, maintaining, and promoting the adoption of standards, components, processes, and tools that support the broader function of Data Management. Additionally, you will have the opportunity to collaborate with Corporate Investment Bank Technology, Global Technology, and other Lines of Business to develop contemporary and innovative engineering methods. Job responsibilities Actively engage with development teams to use, develop, and improve Information Architecture standards, tools, and processes as part of the development process. Provides feedback and proposes improvements to architecture governance practices. Collaborate to create, maintain, govern, and use Controlled Vocabularies with Business Partners and the Chief Data Office. Create and maintain accurate, complete, and consistent governed Data Models with lineage and metadata to facilitate traceability to other metadata classification such as Data Concepts. Guides evaluation of current technology and leads evaluation of new technologies using existing standards and frameworks. Regularly provides technical guidance and direction to support the business and its technical teams, contractors, and vendors. Drives decisions that influence product design, application functionality, and technical operations and processes. Serves as a function-wide subject matter expert in one or more areas of focus. Standardize and innovate Operational and Analytical Data Management in accordance with Reference Architectures and Operating Models. Adds to team culture of diversity, opportunity, inclusion, and respect. Required qualifications, capabilities, and skills Hands-on practical experience delivering system design, application development, testing, and operational stability Software Engineering experience in a data-centric role with exposure to how data is stored, moved, governed, and/or validated/cleaned using Programming Languages such as Java, JavaScript, or Python. Experience in Data Modelling and Architecture tools such as ERwin, Power Designer, and/or Magic Draw or wider use of UML tools or IDEs that integrate modeling tools such as Eclipse. Advanced knowledge of software architecture, applications, and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, 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 Knowledge of some Data Management technologies such as Relational and Columnar Databases, and/or Data Integration (ETL) or API development. Knowledge of some Data Formats such as JSON, XML, and binary formats such as Avro or Google Protocol Buffers. Experience collaborating with business and technical teams to understand, translate, review, and playback requirements and collaborate to develop Model Engineering solutions. Exposure to working with data sets through tools like SQL, JavaScript, or Python. Adds to team culture of diversity, opportunity, inclusion, and respect Preferred qualifications, capabilities, and skills Knowledge of Programming Language Design and Implementation. Management, Data Quality, Metadata Management, Data Taxonomy and Classification, and Security and Protection. Knowledge of Financial Services, specifically Wholesale and Investment Banking. Experience in other Data Standards (preferably Financial) such as SWIFT, FIX, or FpML. Knowledge and experience of Software Engineering Methodologies (e.g., Agile). A willingness to bring an outside perspective to the team, ask questions, and learn from the breadth and depth of experience of the current IA team. An ability to envisage and compare potential solutions prior to implementation