Cloud big data architect

Develop detailed cost and timeline plans for (multi-)cloud modernization data infrastructure, including interim numbers, long-term payoffs, cost avoidance, and increased compliance for complex, high-volume datasets with a variety of mission-based requirements and access permissions. Plans must detail minimum and maximum data infrastructure to simplify policy requirements, including centralized storage, a database, public access, a GIS server component, data layers or mesh to minimize data egress, and tools such as data packaging utilities.

Establish governance standards and define the logical structure for each data domain while developing tailored microservices for high priority and capacity data including real-time streams.

Provide foundational support for Artificial Intelligence (AI) Development efforts including designing for the MLOps Lifecycle, supporting diverse AI workloads, and simplifying AI access and capacity across NOS including video data analysis.

Develop reporting capacity and data analytics infrastructure.

Support the development of new programs and infrastructure requirements.

Core Technical Competencies

Data Warehousing and ETL/ELT Processes o Designing, implementing, and managing large-scale data warehouses and the data pipelines that populate them. Proficiency with enterprise-grade data integration tools and transformation techniques is critical.

Big Data Technology:Proficiency with big data ecosystems and frameworks designed for distributed processing of large datasets in distributed cloud-native frameworks.

Data Modeling and Database Design:Experience in design for structured and unstructured data and technology selection based on use case, performance requirements, and data type.

Data Governance, Security, and Quality:Capable of designing frameworks that enforce data policies, standards, and procedures to maintain data integrity and fitness for use. Metadata management is key.

Leadership and Project Management:Proficient in managing large, modern, complex data projects, prioritizing tasks, guiding and mentoring teammates, and executing on time and within budget while fostering a culture of excellence and setting technical standards.

Stakeholder Management and Communication:Ability to be a central communication hub, acting as a bridge between highly technical teams and non-technical stakeholders. Must be able to articulate complex technical designs, and their implications in clear, concise language.