Data Intelligence Architect

As a Data Intelligence Architect supporting a premier Randstad client in the Washington, DC area, you will serve as the strategic bridge between complex technical infrastructure and actionable business intelligence. You will not only design and maintain sophisticated data, analytics, and AI products but also act as a primary catalyst for organizational change by spearheading data literacy initiatives. By blending high-level architectural design with hands-on mentorship and prompt engineering, you will empower cross-functional teams to leverage generative AI and advanced visualization tools, ultimately fostering a data-driven culture that scales across the enterprise.

Key Responsibilities

• Architectural Design & Product Management: Design, develop, and maintain end-to-end data, analytics, and AI products that ensure insights are accessible and impactful across the organization.
• Strategic Collaboration: Partner with diverse departments to translate complex business requirements into tailored, innovative analytics solutions.
• Data Literacy & Enablement: Lead the design and delivery of workshops, training modules, and educational materials to elevate AI and data literacy for all staff levels.
• Mentorship & Best Practices: Guide analysts and stakeholders on data visualization standards, advanced analytics techniques, and the optimal use of self-service tools.
• Culture & Storytelling: Champion an integrated analytics culture by sharing compelling data stories and promoting collaborative decision-making across the firm.
• Governance & Documentation: Establish and maintain robust documentation, guidelines, and governance standards for analytics processes and AI tool utilization.
• Performance Monitoring: Track and report on the business impact and ROI of data and AI initiatives to drive continuous improvement and innovation.

Required Skills and Qualifications

• Technical Expertise: Proven experience in dimensional data modeling, data warehousing solutions, and the full software development lifecycle (SDLC).
• AI & Data Science: Deep proficiency in machine learning and AI concepts, including practical application of generative AI tools and prompt engineering.
• Visualization & Analysis: Expert-level skills in platforms such as Tableau or Power BI, complemented by strong SQL and programming proficiency in Python or R.
• Communication Excellence: Exceptional ability to distill complex technical concepts into clear, persuasive presentations for non-technical executive audiences.
• Governance Knowledge: Strong understanding of data quality, security, and governance principles within a highly regulated environment.
• Local Presence: Ability to support our client in the Washington, DC area, navigating the specific professional landscape of the region.