Enterprise Data Architect

About the role

About Working at Commerce Building a career here is more than just steps on a ladder. It's about helping people find financial safety and success, helping businesses thrive, and making sure people and their money are taken care of. And our commitment doesn't stop there. Our culture is about our people, the ones in our communities and the ones that work with us. Here, you'll find opportunities to grow and learn, to connect with others, and build relationships with the people around you. You'll have the space and resources to grow into the best version of yourself. Because our number one investment is you. Creating an award-winning culture doesn't come easy. And after 160 years, we know Commerce Bank is only at its best when our people are. If this sounds interesting to you, keep reading and let's talk. Compensation Range Annual Salary: $105,000.00 - $123,500.00 (Amount based on relevant experience, skills, and competencies.) About This Job The main purpose of this job is to collaborate with the Enterprise Architecture program and business data stakeholders to ensure that the technical architecture and information ecosystem would enable the organization to achieve business outcomes and generate meaningful value from its data assets. The Data Architect is responsible for discovering & documenting the data and analytics requirements for information for all uses and requires a deep understanding of data management, data modeling, data warehousing and emerging data integration technologies. Work Schedule Monday - Friday 8:00 AM - 5:00 PM Essential Functions Partner with business and technical leadership to provide strategic recommendations that maximize the value of data assets via their creation, access and use Analyze and optimize data models for performance, scalability and cost effectiveness in the cloud. Collaborate with IT Architecture, Information Security, and Data Governance stakeholders to define standards and policies for data lifecycle management, data keying strategy, and data obfuscation strategy Monitor and assess the benefits and risks of change impacting the data ecosystem (i.e. new system implementations, deployment of new tools and utilities, etc.) Actively work to mitigate the negative impact of change affecting the use of data architecture. Provide the organization with a future-state view of the business data landscape that minimizes restrictions imposed by proprietary solutions or technologies. Collaborate in the process of architectural planning and influence decisions on data architectural design. Assist data, analytic, business and IT leaders in developing data governance processes and structures. Facilitate design sessions with business and technology stakeholders to understand business needs and requirements. Develop and manage data blueprints and information models (i.e. conceptual models, logical models, physical models, relational database designs, dimensional modeling, data vault, message models and others) Proactively manage the classification and zoning of data assets sourced from systems, applications, and external third-party information providers to increase time to value Aid efforts to improve business performance through enterprise information solutions and capabilities, such as master data management (MDM), metadata management, analytics, content management, data integration, and related information management or information infrastructure components Analyze data and analytics security requirements and solutions, and partner with leadership to ensure that enterprise business data and analytics assets are protected. Perform other duties as assigned Knowledge, Skills & Abilities Required Strong understanding of system integration, including interface design, and familiarity with web-oriented architecture techniques. Strong understanding of data modeling and information classification expertise at the enterprise level and industry-specific knowledge of data security protocols, policies, and regulations Strong understanding of common information architecture frameworks and information models Strong understanding of metamodels, taxonomies and ontologies, as well as of the challenges of applying structured techniques (data modeling) to less-structured sources Strong understanding of data science concepts, as well as MDM, business intelligence, and data warehouse design and implementation techniques Strong understanding of a variety of data access and analytics approaches (for example, microservices and event-based architectures) Strong understanding with enterprise architecture modeling languages or frameworks such as TOGAF, ArchiMate, Zachman or UML Ability to develop positive relationships across business and technical domains to facilitate activity that produces mutually beneficial outcomes Ability to assess rapidly changing technological trends and developments and apply them to business needs Ability to understand problems from a broad perspective

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