Lead Cloud Solution Architect- AI & Data (AWS)

Requirements

• Minimum 10 years of progressive experience in data architecture, data engineering, cloud architecture, or related technical disciplines
• Minimum 7 years of hands-on experience designing, deploying, and operating data and AI workloads on AWS in enterprise environments
• Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience
• Demonstrated real-world experience designing and delivering enterprise data platforms, including data lakes, data warehouses, streaming architectures, and data governance frameworks
• Deep expertise in AWS data and AI platform services: Redshift, Glue, Lake Formation, Kinesis, EMR, Athena, SageMaker, Bedrock, and related ecosystem services
• Proven hands-on experience with Databricks or Snowflake deployed on AWS in enterprise environments
• Demonstrated experience designing AI-ready data architectures, including data preparation pipelines, vector stores, retrieval-augmented generation (RAG) patterns, and AI governance frameworks
• Proven ability to develop and articulate AI & Data business cases, connecting technical architecture decisions to client outcomes and measurable business value
• Experience authoring SOWs, LOEs, reference architectures, and delivery playbooks that technical teams can execute from
• Strong communication skills, able to present data and AI architecture concepts to executive audiences and technical depth to delivery teams with equal effectiveness
• Strongly Desired Skills
• AWS Certifications
• AWS Certified Solutions Architect: Professional (strongly preferred)
• AWS Certified Data Engineer: Associate or Professional
• AWS Certified Machine Learning: Specialty
• Platform Certifications
• Databricks Certified Data Engineer (Associate or Professional)
• Snowflake SnowPro Core or Advanced: Data Engineer
• Technical Depth
• Enterprise data architecture patterns: data lakehouse, data mesh, data fabric, medallion architecture
• Data pipeline and orchestration tooling: Apache Airflow, AWS Step Functions, Glue workflows, dbt
• Streaming and real-time data architectures: Kinesis Data Streams, Kafka on AWS (MSK), EventBridge
• Data governance and cataloging: AWS Lake Formation, Glue Data Catalog, data lineage and quality frameworks
• AI operationalization on AWS: Bedrock, RAG architecture design, agentic workflow patterns, prompt engineering, AI governance
• Vector database and embedding patterns relevant to enterprise AI workloads
• SageMaker for model deployment, inference, and MLOps; experience with model training is a differentiator
• Application security patterns relevant to data and AI (data access controls, PII handling, model governance)
• Cloud cost modeling and FinOps principles as applied to data platform architecture decisions
• Multi-Cloud Exposure
• Familiarity with Azure data and AI services (Azure Synapse, Azure Data Factory, Azure AI Foundry, Microsoft Fabric)
• Experience advising clients on multi-cloud data strategy or workload placement decisions across AWS and Azure
• Microsoft Azure certifications (any level) are a plus
• What Success Looks Like in Year One
• WWT's AI & Data service offerings are sharper, more repeatable, and faster to scope, measurably reducing presales cycle time
• Solution Architects trust this role as their go-to technical escalation for AI & Data pursuits
• Delivery oversight has prevented at least one significant architectural problem from reaching the client
• The frameworks, playbooks, and standards this role has built have made WWT's AI & Data delivery more scalable, enabling the team to take on greater volume without sacrificing quality
• Client satisfaction scores on AI & Data engagements reflect a measurable improvement in delivery consistency and outcome achievement
• Want to learn more about Consulting Services? Check us out on our platform:
• https://www.wwt.com/consulting-services
• The well-being of WWT employees is essential. So, when it comes to our benefits package, WWT has one of the best. We offer the following benefits to all full-time employees:
• Health and Wellbeing: Health, Dental, and Vision Care, Onsite Health Centers, Employee Assistance Program, Wellness program
• Financial Benefits: Competitive pay, Profit Sharing, 401k Plan with Company Matching, Life and Disability Insurance, Tuition Reimbursement
• Paid

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