<h2>Qualifications</h2>
<ul>
<li>Minimum 10 years of progressive experience in data architecture, data engineering, cloud architecture, or related technical disciplines</li>
<li>Minimum 7 years of hands-on experience designing, deploying, and operating data and AI workloads on AWS in enterprise environments</li>
<li>Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent practical experience</li>
<li>Demonstrated real-world experience designing and delivering enterprise data platforms, including data lakes, data warehouses, streaming architectures, and data governance frameworks</li>
<li>Deep expertise in AWS data and AI platform services: Redshift, Glue, Lake Formation, Kinesis, EMR, Athena, SageMaker, Bedrock, and related ecosystem services</li>
<li>Proven hands-on experience with Databricks or Snowflake deployed on AWS in enterprise environments</li>
<li>Demonstrated experience designing AI-ready data architectures, including data preparation pipelines, vector stores, retrieval-augmented generation (RAG) patterns, and AI governance frameworks</li>
<li>Proven ability to develop and articulate AI & Data business cases, connecting technical architecture decisions to client outcomes and measurable business value</li>
<li>Experience authoring SOWs, LOEs, reference architectures, and delivery playbooks that technical teams can execute from</li>
<li>Strong communication skills, able to present data and AI architecture concepts to executive audiences and technical depth to delivery teams with equal effectiveness</li>
</ul>
<p><strong>Strongly Desired Skills</strong></p>
<h3>AWS Certifications</h3>
<ul>
<li>AWS Certified Solutions Architect: Professional (strongly preferred)</li>
<li>AWS Certified Data Engineer: Associate or Professional</li>
<li>AWS Certified Machine Learning: Specialty</li>
</ul>
<h3>Platform Certifications</h3>
<ul>
<li>Databricks Certified Data Engineer (Associate or Professional)</li>
<li>Snowflake SnowPro Core or A