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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).

Experience with metadata management and automation tools is highly desirable.

Preferred qualifications, capabilities, and skills

• 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.

Continuous learner, staying abreast of industry trends and emerging technologies.