The position is intended to provide architectural direction and leadership in the selection and implementation of complex database, analytical, data integration and data management systems, in support of the needs and objectives of the Organizational Units of the IEEE. The individual in this role will help driving the IEEE data strategy, provide architectural oversight to data and analytical components of all major implementations, lead migration of on-prem data-intensive workloads to the cloud, optimize the existing data-intensive workloads and facilitate governance and streamlining operations of compute and storage resources used in these implementations.
The role reports to Senior Manager for IT Enterprise Architecture and functions as an individual contributor. The role requires a self-starter that can be productive with minimal direction.
Specific duties include but not limited to:
Designs and implements effective database solutions and data models for transactional and analytical systems in AWS cloud, on-prem and hybrid cloud
Designs data persistence, retrieval, integration, disaster recovery and management by application and business continuity requirements.
Conducts fit-for-purpose assessment of relational, no-SQL, graph and other database solutions, depending on requirements
Develops and manages data warehouse architectures and designs for on-prem, AWS cloud and hybrid systems.
Develops and maintains data strategy and policies.
Prepares accurate database design and architecture reports for management and executive teams.
Partners with leadership to develop and enforce technology standards and ensure that business information needs are understood and mapped to feasible architectures and infrastructures
Reviews project requirements, evaluating industry-strength XaaS solutions and providing architectural recommendation based on data integration considerations
Analyzes feedback from user interviews, usability studies and focus groups, translate analysis into design decisions, and manage exceptions to standards
Identifies key technology overlaps and gaps and formulating strategies to optimize database technology spend, efficiency and effectiveness
Analyzes complex legacy systems and come up with cloud migration strategies with particular focus on underlying data architectures