Lead Architect - Information Architect - Vice President in Bournemouth

Overview

As a Lead Architect at JPMorgan Chase within the Corporate Investment Bank Information Architecture team, you contribute to high‑quality architecture solutions for software applications and platform products.

You influence target state architecture across multiple domains and drive the adoption of standards, components, processes, and tools that support Data Management.

You collaborate with Corporate Investment Bank Technology, Global Technology, and other lines of business to develop contemporary engineering methods, and you engage with development teams to use, develop, and improve Information Architecture standards, tools, and processes as part of the development lifecycle.

You provide feedback and propose improvements to architecture governance practices and work with Business Partners and the Chief Data Office to create and maintain governed data models with lineage and metadata for traceability.

You guide evaluation of current technology and lead the evaluation of new technologies using existing standards and frameworks.

You offer technical guidance to support the business, its technical teams, contractors, and vendors, and influence product design, application functionality, and operational processes.

You serve as a function‑wide subject matter expert in one or more areas of focus and standardize and innovate operational and analytical data management in alignment with reference architectures and operating models.

You contribute to a team culture of diversity, opportunity, inclusion, and respect.

Responsibilities

• Provide hands‑on practical experience delivering system design, application development, testing, and operational stability within a data‑centric role.
• Apply software engineering experience in data storage, movement, governance, and data cleansing using languages such as Java, Java Script, or Python.
• Engage in data modeling and use architecture tools (e. g., ERwin, Power Designer, Magic Draw) or UML/IDE integrations to model systems and data flows.
• Evaluate current and emerging technologies, influencing future state architectures using established standards and frameworks.
• Collaborate with business and technical teams to understand and translate requirements, and develop Model Engineering solutions.
• Collaborate to create, maintain, govern, and use controlled vocabularies with business partners and the Chief Data Office.
• Ensure accurate, complete, and consistent governed data models with lineage and metadata for traceability to metadata classifications.
• Provide ongoing technical guidance to support business and technical teams, contractors, and vendors.
• Standardize and innovate data management practices in accordance with reference architectures and operating models.

Qualifications

• Hands‑on experience delivering system design, application development, testing, and operational stability in a data‑centric role; exposure to data storage, movement, governance, and data cleansing; programming languages include Java, Java Script, or Python.
• Experience with data modeling and architecture tools (ERwin, Power Designer, Magic Draw) or UML tools and IDEs with modeling capabilities.
• Advanced knowledge of software architecture and technical processes with depth in one or more areas (e. g., cloud, AI/ML, mobile).
• Ability to tackle design and functionality problems independently with limited oversight.
• Ability to evaluate current and emerging technologies to recommend solutions for future state architecture.
• Knowledge of data management technologies (relational and columnar databases, ETL/data integration, API development) and data formats (JSON, XML, Avro, Protocol Buffers).
• Experience collaborating with business and technical teams to translate requirements into Model Engineering solutions and working with data sets using SQL, Java Script, or Python.
• Commitment to diversity, opportunity, inclusion, and respect within the team culture.
• Preferred qualifications, capabilities, and skills
• Knowledge of programming language design and implementation.
• Experience with data quality, metadata management, data taxonomy/classification, and data security and protection.
• Knowledge of financial services, specifically wholesale and investment banking.
• Experience with data standards (preferably financial) such as SWIFT, FIX, or Fp ML.
• Knowledge and experience of software engineering methodologies (e. g., Agile).
• A willingness to bring an outside perspective, ask questions, and learn from the IA team.
• Ability to envisage and compare potential solutions prior to implementation.
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