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Job description
Description The Amazon Web Services Professional Services (ProServe) team is seeking a Delivery Consultant specializing in Data to join our Healthcare and Life Sciences (HCLS) practice. You will be at the center of the most consequential shift in enterprise technology: making organizations truly AI-ready. Every agentic AI system, every foundation model grounded in enterprise knowledge, and every GenAI application that moves from prototype to production depends on the data layer beneath it - and that's what you build.
Description The Amazon Web Services Professional Services (ProServe) team is seeking a Delivery Consultant specializing in Data to join our Healthcare and Life Sciences (HCLS) practice. You will be at the center of the most consequential shift in enterprise technology: making organizations truly AI-ready. Every agentic AI system, every foundation model grounded in enterprise knowledge, and every GenAI application that moves from prototype to production depends on the data layer beneath it - and that's what you build.
You will design and implement modern data platforms (lake, lakehouse, mesh), architect data pipelines that transform raw, fragmented data estates into governed, AI-ready assets; and design and implement enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graph architectures that allow foundation models and AI agents to reason accurately, access data securely, and execute autonomously within regulated environments. You will work hands-on inside HCLS customer environments with complex data lineage, regulatory overlays (GxP, HIPAA, CDISC), and legacy systems, and ship production-grade data products that serve multiple downstream consumers, from ML model training to agentic orchestration layers.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using AWS services. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing and AI transformation initiatives.
This role requires approximately 50% co-location on site with customer, AWS and partner teams within the U.S.
Key job responsibilities
Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures within enterprise HCLS environments, integrating with legacy systems and existing data governance frameworks
Build data products that serve multiple downstream applications and use cases — from AI/ML model training to agentic AI systems, ensuring data quality, lineage, and reliability at scale
Operate with a high degree of autonomy within fast-moving delivery engagements, making judgment calls on data modeling, pipeline design, and architecture without waiting for perfect specifications or constant oversight
Navigate complex data access, security, and privacy requirements unique to pharma and healthcare including GxP compliance constraints, HIPAA, and regulatory data governance frameworks
Architect contextual knowledge layers, including ontologies and knowledge graphs leveraging AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions to equip AI agents with the vocabulary and guardrails to reason accurately and execute autonomously within regulated environments
Collaborate across organizational boundaries to secure data access, understand source system context, and resolve data quality challenges with teams across customer IT, business, and partner organizations
Deliver iteratively when requirements are ambiguous, translating incomplete business needs into well-architected data solutions that can evolve as customer understanding matures
Apply AI-DLC (AI-accelerated Development Life Cycle) methodologies to data delivery to redesign data workflows to become AI-native for accelerated scale and pace
About The Team
ABOUT AWS:
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Basic Qualifications
5+ years of cloud architecture and solution implementation experience
Bachelor's degree, or 7+ years of professional or military experience
5+ years of experience in data engineering, data architecture, and/or data platform development, with hands‑on implementation of production data pipelines
Experience with modern data platform design patterns, including data lakes,
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Worksite address
mountain view, CA, 94039, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.