Duties: Build, run, and govern enterprise data lake, Data-as-Service, and BI architecture. Define data architectural patterns/anti-patterns and overall strategy of enterprise Data Lake to support business with changing demands and technology trends. Responsible for R&D/POC/POV of new technologies and evangelizing those technologies. Provide architectural vision, planning, and technical leadership for supported applications, data lakes, analytics, or IT system processes, helping to evaluate, develop, implement, and monitor technology and programming standards throughout the IT operational areas. Provide technical leadership and direction for large-sized, enterprise-level systems planning or systems implementation teams, helping to manage progress toward required technical deliverables to assure overall project success. Mentor and develop other technical resources to help ensure team members follow best practices that lead to optimal project success. Provide expert-level disaster recovery, business continuity planning, and IT contingency strategy design work. Elicit information and viewpoints from a variety of individuals to help plan, design, and architect technical solutions. Lead complex data projects that demand special technical knowledge - Cloud, AI/ML. Define solution architecture that include systems context, ETL flow definitions, and technology decisions on both Data Lake and BI projects. Influencing solutions that are dependent on data and the long-term development of data lake, reporting, and analytics platforms. Create POCs and POVs for technology and solutions as a hands-on architect.
Requirements: Bachelor’s degree in computer science, computer information systems, computer engineering, software engineering, industrial and systems engineering, or a related field plus 96 months of experience in advanced system development, support, analysis, or architectural design and 60 months of data architecture experience in a complex, multi-platform distributed environment. Also requires in-depth knowledge of IT concepts, strategies, and data architecture methodologies; proficiency in data quality, metadata management, data discovery, reporting, and analytics, and demonstrated ability to develop and maintain contextual architectural planning and current state systems diagrams that accurately capture systems and data flow representations.