Lead Data Architect
at J.P. Morgan
Posted 16 hours ago
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- Compensation
- Not specified
- City
- Not specified
- Country
- United States
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Lead Architect for Data products within Corporate Oversight and Governance Technology (COGT) at JPMorgan Chase. You will drive architecture solutions for data across multiple business functions, including design of logical and physical data models, data mesh adoption, and federated data sharing. The role focuses on scalable, secure data solutions aligned with enterprise standards, metadata management, data quality, and governance, while providing technical guidance and mentorship to data engineering, governance, and application teams. You will deliver data products on modern cloud-based platforms and continuously seek improvements in automation and platform capabilities.
Location: OH, United States
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As a Lead Architect for Data products at Corporate Oversight and Governance Technology (COGT) with in the Corporate technology LOB, you are an integral part of a team that works to develop high-quality architecture solutions for various software applications on modern cloud-based technologies. As a core technical contributor, you are responsible for conducting critical architecture solutions across multiple technical areas within various business functions in support of project goals.
Job responsibilities
- Represent the data architecture team at technical governance bodies, providing feedback and proposing improvements to governance practices.
- Guide evaluation of current and emerging technologies, leading assessments using established data architecture standards and frameworks.
- Design, develop, and maintain logical and physical data models (e.g., using Erwin Data Modeler), optimizing architectures for automation and integration with enterprise platforms.
- Architect and implement scalable, secure, and reliable data solutions, ensuring alignment with enterprise standards.
- Champion and implement data mesh methodologies to enable decentralized data ownership and self-serve data infrastructure.
- Coordinate and facilitate federated data sharing across business units and application teams, ensuring secure and efficient data exchange.
- Lead and coordinate research, development, and implementation of data products, collaborating with stakeholders to define requirements and ensure successful delivery.
- Drive automation of metadata management processes to enhance data discoverability, lineage, and governance; implement tools and frameworks for metadata capture and cataloging.
- Advise teams on database selection and data storage design, including normalization principles and best practices, considering scalability, performance, and cost.
- Guide teams on Trusted Data Quality (TDQ) principles and implementation patterns to ensure high-quality, reliable data across applications and platforms.
- Design and enforce data transfer control procedures for secure and compliant data movement between OLTP applications and data lakes; architect and promote common APIs/tools for standardized data transfer.
- Provide technical guidance, mentorship, and best practices to application development, data engineering, and governance teams, including junior architects and technologists.
- Ensure data quality, security, and compliance with regulatory standards and firmwide policies.
- Actively contribute to the engineering community, advocating for data frameworks, tools, and practices throughout the Software Development Life Cycle (SDLC).
- Identify opportunities for continuous improvement in data automation, platform capabilities, and data product offerings.
- Serve as a function-wide subject matter expert in one or more areas of focus.
Required qualifications, capabilities, and skills
- Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
- Formal training or certification in Data Architecture concepts.
- 5+ years of applied experience in data architecture, data engineering, or a related discipline.
- Hands-on practical experience delivering system design, application development, testing, and operational stability.
- Advanced proficiency in one or more programming languages, applications, and architecture.
- Experience with data modeling tools (e.g., Erwin Data Modeler).
- Experience with big data processing frameworks (e.g., Spark).
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Experience with metadata management and automation tools is highly desirable.
- Strong Communication, collaboration, analytical and problem-solving abilities.
- Ability to independently tackle complex design and functionality problems with little to no oversight.
- Understanding of data mesh concepts and practical experience implementing data mesh methodologies.
- Experience coordinating federated data sharing and data product development in large, complex enterprise environments.
- Knowledge of data governance, data quality (including TDQ principles), and compliance best practices.
- Ability to evaluate current and emerging technologies to select or recommend optimal solutions for future-state architecture.
- Leadership in mentoring teams, establishing best practices, and driving adoption of innovative technologies.
- Commitment to fostering a team culture of diversity, opportunity, inclusion, and respect.
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Continuous learner, staying abreast of industry trends and emerging technologies.
