Orlando, FL 32801
Join our clients growing Data team as an Enterprise Data Architect. This is a full-time role. Competetive salary and benefits. We are looking for someone with the following experience.
- Technical Expertise
- Expertise in data architecture and design for both structured and unstructured data.
- Expertise in data modeling.
- Understanding of Solutions Architecture methodology and practices.
- Deep familiarity working with relational database systems, including Microsoft SQL Server or similar.
- Knowledge of Master Data Management solutions.
- Strong knowledge and experience with data warehouses and data marts, including a strong understanding of the Kimball Methodology.
- Understanding of how Data Lakes work, and what their place is in an Operating Platform Model.
- Oversee and approve design of data solutions for projects and programs, collaborating with the Enterprise and Solution Architects for the overall solution design approach.
- Oversee and lead the design of data integration for enterprise systems, including integration to SaaS and COTS solutions.
- Define and maintain a holistic data strategy for the Enterprise, including reference architectures and design patterns.
- Partner with IT Plan, Build, and Run teams on the implementation of the data designs.
- Provide hands-on expert level assistance to the Project/Product Delivery Team Members for technical issues.
- Fluency in cloud-based data storage offerings.
- Lead and Influence
- Provide thought leadership, technical specialty, and mentorship to project teams throughout the project lifecycle.
- Influence and collaborate with fellow leaders on the Architecture Guidance Team (AGT) to vet and define technology standards and best practices.
- Strong consensus-building and negotiating skills.
- Focus on Strategy and Execution
- Focus on delivering practical, working solutions.
- Lead design of high performance, highly scalable and flexible, secure, cost-effective data solutions that meet business requirements and conform to architectural design and technology strategies.
- Develop and promote reference architectures for enterprise solutions.
- Consult with IT Delivery and Operations partners to ensure alignment of the solution approach with their respective abilities to execute and manage the solution delivery and operations, ensuring consistency with the enterprise architecture, as well as identifying when it is necessary to modify the enterprise architecture.
- Work with various business stakeholders in problem solving, creating business capabilities, and defining effective and efficient technology solutions for solving business problems and enabling business capabilities.
- Overall data design and modeling across all of the organization’s data systems, especially for major data platforms (data warehouses, data lakes, master data management).
- Data management responsibilities across multiple data systems: data governance, data mastering, metadata management, data definitions, semantic-layer design, taxonomies, etc.
- Architecting and delivering highly scalable and flexible, yet cost effective, enterprise data solutions.
- Architects the future state solution for projects, leveraging existing platforms where appropriate.
- Establish the technology strategy and roadmaps for the portfolio of data platforms and services across the organization.
- Data security and compliance.
- Designing and documenting data architecture at multiple levels (high-level to detailed) and across multiple views (conceptual, logical, physical, data flow, and sequence diagrams).
- Providing active “hands-on” architectural guidance and leadership through the entire lifecycle of development projects.
- Translating business requirements into conceptual and detailed technology solutions.
- Building proof-of-concept systems as needed in order to demonstrate how a platform would work to solve specific business challenges.
- Working with business partners and the Data Governance Committee to govern attributes in relation to master data domains.
- Maintaining fluency with data advancements in the industry and marketplace and staying current with vendor product offerings and common and emerging technologies; continuously learning new data technologies and introducing these into the organization, where appropriate.
- Cross-training peers and mentoring teammates.