Data Solutions Architect

The Data Solutions Architect is a strategic role within the organization, responsible for designing data and cloud technology solutions that meet business requirements while adhering to best practices and aligning with the enterprise data architecture. The Data Solutions Architect acts as the bridge between business objectives and technology solutions, ensuring that the data capabilities and data platform created are robust, scalable, and secure. This position requires a comprehensive understanding of both business processes and technical capabilities. The Data Solutions Architect will be expected to be hands-on technically, but also present to leadership and lead projects.

Job Duties and Responsibilities:

Solutions Design (25%)

• Analyze Business Requirements: Work closely with stakeholders to understand functional and non-functional requirements for the data solution.

• Define Architecture Components: Identify and design data components, including data flow, integration points, interfaces, and overall architecture.

• Create Architecture Diagrams: Develop high-level and detailed diagrams (e.g., flowcharts, sequence diagrams, system interaction models) to represent the solution architecture.

• Select Appropriate Technologies: Choose frameworks, languages, and tools that align with the architecture, ensuring they meet both current needs and scalability requirements.

• Ensure Scalability and Security: Design the solution to be scalable, reliable, and secure, incorporating security standards and performance considerations.

• Assess the Impact of Architectural Decisions: Evaluate how design choices impact current and future systems, ensuring they fit within the broader enterprise architecture.

Stakeholder Collaboration (20%)

• Gather Requirements with Stakeholders: Facilitate workshops and meetings with business analysts, project managers, developers, and other stakeholders to understand project needs.

• Communicate Design Decisions: Explain architectural decisions and solution designs to non-technical stakeholders in an understandable way, including how the design aligns with business goals.

• Coordinate with Development Teams: Work with development leads to align project timelines, resource allocation, and technical requirements.

• Participate in Project Meetings: Attend regular project updates and stand-ups to align with project status and provide architecture-related guidance.

• Resolve Conflicts: Address and resolve any misunderstandings or misalignments between technical and business stakeholders regarding project scope and design.

Technical Leadership and Oversight (20%)

• Provide Technical Guidance: Offer ongoing guidance to the development team, helping them align with the data solution architecture.

• Code Reviews and Quality Assurance: Review code and design work to ensure compliance with architectural standards and best practices.

• Assist in Troubleshooting and Debugging: Help resolve any technical challenges, especially those related to architectural constraints or requirements.

• Enforce Best Practices: Ensure the use of best practices in areas like coding standards, API design, integration methods, and performance optimization.

• Evaluate Technical Debt: Identify and address technical debt areas to ensure the maintainability and scalability of the solution.

Documentation (15%)

• Prepare Architecture Documentation: Create and maintain detailed documentation that outlines the architecture, including design specifications and component details.

• Maintain Technical Roadmaps: Develop roadmaps for technical implementation and deployment and update these based on project evolution.

• Document Key Decisions and Assumptions: Record major architectural decisions, assumptions, and rationales to provide context for future reference.

• Create User Guides and Training Materials: As necessary, prepare materials to help other teams understand and use the architecture effectively.

• Update and Archive Documentation: Ensure all documentation is current and accessible, archiving outdated materials as the project progresses.

Evaluation of Technologies, Training and Prototyping (10%)

• Research New Tools and Frameworks: Continuously research emerging tools, libraries, and frameworks that could improve the solution architecture.

• Develop Proof of Concepts (POCs): Create small-scale prototypes to test and validate new technologies or architecture approaches.

• Evaluate Technology Fit: Assess whether new technologies fit within the existing e