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Genzeon - Data Architect - Data Modeling & Governance
3 months ago
Job Description :
The Enterprise Data Architect is critical in supporting the expansion of enterprise-wide data management initiative. Collaborating closely with the Enterprise Architecture program and critical business data stakeholders, your primary objective is to ensure that the technical architecture and information ecosystem align seamlessly with business objectives, thereby driving significant value from our data assets.
This position will guide strategic technology decisions within the realm of business data, while also formulating and implementing policies, practices, and standards to uphold these decisions.
Your collaboration with business and technical leaders will oversee and enhance technology architectures to ensure their sustainability, suitability, and compliance with industry regulations, legal requirements, ethical guidelines, and corporate policies.
As the Enterprise Data Architect, you will be responsible for the comprehensive discovery and documentation of data and analytics requirements for all information utilization purposes.
Essential Job Functions :
- Data Modeling and Management: Develop and maintain conceptual, logical, and physical data models, recommend data architecture components, and utilize data modeling techniques for practical data understanding and alignment with business concepts.
- Collaboration and Stakeholder Engagement: Collaborate with cross-functional teams, including data stewards, analysts, and technology groups, to ensure data solutions meet business needs and support current and future data management requirements.
- Data Quality and Consistency: Work with technology teams to implement data models, ensuring data quality, integrity, and consistency throughout the data lifecycle.
- Enterprise Data Strategy: Contribute to and maintain enterprise data architecture models and roadmaps in alignment with core business capabilities, processes, and IT strategies.
- Industry Knowledge: Stay current with industry trends, data modeling, and management techniques advancements.
- Strategic Recommendations: Partner with business and technical leadership to provide strategic recommendations for maximizing the value of data assets and influencing data architectural decisions.
- Data Governance and Compliance: Work with business and IT teams in developing data governance processes, standards, and policies for data lifecycle management, data security, and compliance.
- Data Blueprint and Information Models: Consult with business and technology stakeholders to develop and manage data blueprints and information models, encompassing various data model types.
- Data Asset Management: Proactively manage the classification and zoning of data assets from diverse sources to accelerate value realization.
- Enhancing Business Performance: Drive 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 data security.
- Change Management: Monitor and assess the impact of changes on the data ecosystem, actively working to mitigate negative effects and ensuring alignment with data architecture.
- Future-State Vision: Provide a forward-looking view of the business data landscape, minimizing reliance on proprietary solutions or technologies.
Specific Skills/ Attributes :
- Proficiency in core data services, encompassing the management of data lakes, data warehouses, data marts, relational and dimensional modeling, data quality assurance, and master data management.
- Exceptional data management and governance skills, including aligning data architectures that recognize data as a valuable organizational asset.
- Experience and understanding of AI and machine learning concepts, including their integration with data architecture for advanced analytics and decision support.
- Knowledge and familiarity with contemporary data architecture principles and practices.
- An advanced understanding of system integration, encompassing interface design, along with a grasp of web-oriented architecture techniques.
- Advanced expertise in data modeling and information classification at the enterprise level and industry-specific knowledge of data security protocols, policies, and regulations.
- A strong understanding of common information architecture frameworks and information models.
- Proficiency in metamodels, taxonomies, and ontologies, with an appreciation for the challenges of applying structured techniques like data modeling to less-structured data sources.
- A solid understanding of data science concepts and experience in Master Data Management (MDM), business intelligence, and data warehouse design and implementation techniques.
- Advanced knowledge of various data access and analytics approaches, such as APIs, microservices, event-based architectures, and AI-driven analytics.
- The ability to assess rapidly evolving technological trends and developments in AI, machine learning, and data analytics and apply them to meet business needs effectively.
- Proficiency in using business capability models to create an information-centric view that quickly identifies critical information aligned with the organization's defined business strategy.
- The capability to understand problems holistically, leveraging business and technical knowledge to anticipate the impact of issues and propose practical solutions.
- Hands-on experience with AWS data services, including RDS, Health data lake, Data exchange, Glue, Glue catalog, etc.
- Demonstrated excellence in consultative, presentation, oral and written communication skills
- Demonstrated experience and strong knowledge of Systems Development Life Cycle (SDLC) including iterative/agile approaches, Service Life Cycle and Project Management Life Cycle
- Excellent technical knowledge and understanding of architecture, applications, systems design, and integration.
- Broad knowledge of healthcare processes and data linkages across clinical, financial, and patient administrative areas.
- Expert knowledge of Healthcare standards such as FHIR, CCDA, HL&.
- Knowledge of HiTrust / HIPAA, SOX, SOC2 is a plus.
- Strong analytical, critical thinking, troubleshooting, and problem-solving skills.
- Strong innovation, planning, and organization skills.
Qualifications :
- Generally requires 10+ years of related experience, including a proven track record in Data Architect roles focusing on enterprise data architecture.
- Generally requires a bachelor's degree
