Data & AI Solutions Architect

Role Overview

Data & AI Solutions Architect (West Coast US team, remote) working with a boutique technology-focused management and strategy consultancy. You will support client engagements by shaping practical data and AI solutions and designing scalable architectures across enterprise systems and cloud environments.

Key Responsibilities

• Elicit business requirements, identify data needs, and assess technical constraints to define data & AI solutions.
• Design and implement data and AI architectures, including conceptual and logical data models.
• Apply data governance frameworks, standards, and best practices for data quality, security, and regulatory compliance.
• Support evaluation, selection, and integration of data/AI tools and platforms.
• Design data pipelines, integration patterns, and data flows across enterprise systems and cloud environments.
• Collaborate with data engineers and cross-functional teams to deliver solutions aligned with architectural standards.
• Build prototypes and PoCs to validate solution designs before full deployment.
• Create and maintain Infrastructure as Code (IaC) scripts (e.g., Terraform, AWS CloudFormation) for automated cloud provisioning.
• Participate in code and architecture reviews to address technical debt, performance bottlenecks, and scalability/reliability improvements.
• Support modernization efforts, including migration of legacy applications and data to cloud platforms.
• Document data architectures, models, processes, and technical designs.
• Work with stakeholders on data governance, lifecycle management, and enterprise data management.

Requirements

• 2–4 years relevant experience in data engineering, analytics, software development, or similar technical roles.
• Bachelor’s degree in Computer Science/Engineering/Information Systems or related field.
• Basic understanding of data architecture, data modeling, and data integration.
• Familiarity with cloud platforms (Azure, AWS, or GCP) and modern data ecosystems (advantageous).
• Preferred: exposure to data governance, data quality management, and security best practices.
• Working knowledge of SQL and at least one analytics/data tool such as Python and/or Tableau (plus Excel or equivalents).
• Strong analytical/problem-solving skills and client-focused mindset.
• Clear communication and collaboration; hands-on and adaptable approach.

Nice to Have

• Experience with security and compliance practices for enterprise data.
• Familiarity with specific data/AI tools and platforms used in client ecosystems.