Senior Delivery Consultant - Data , Professional Services, AWSI HCLS

About the role

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, foundation model, and GenAI application depends on the data layer beneath it—you will design and implement modern data platforms (lake, lakehouse, mesh), architect data pipelines, and build enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graphs. This role requires approximately 50% co-location on site with customer, AWS, and partner teams within the U.S.

The AWS Professional Services organization is a global team of experts that helps customers realize their desired business outcomes when using AWS services. We collaborate with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing and AI transformation initiatives.

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—from AI/ML model training to agentic AI systems—ensuring data quality, lineage, and reliability at scale.
• Operate with a high degree of autonomy in fast-moving delivery engagements, making judgment calls on data modeling, pipeline design, and architecture without waiting for perfect specifications.
• Navigate complex data access, security, and privacy requirements unique to pharma and healthcare, including GxP compliance, 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 reasoning and execution capabilities in regulated environments.
• Collaborate across organizational boundaries to secure data access, understand source system context, and resolve data quality challenges with customer IT, business, and partner teams.
• Deliver iteratively when requirements are ambiguous, translating incomplete business needs into well-architected data solutions that evolve as customer understanding matures.
• Apply AI-DLC (AI-accelerated Development Life Cycle) methodologies to redesign data workflows for accelerated scale and pace.

Requirements

• 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, lakehouses, data mesh, and zero-ETL patterns and streaming architectures, using services such as Amazon SageMaker Lakehouse, SageMaker Unified Studio, Amazon S3 Tables, Amazon Redshift, and zero-ETL integrations.

Preferred Qualifications

• AWS certifications in Data Analytics or Machine Learning Specialty.
• Experience in the healthcare and life sciences industry, including familiarity with compliance and security frameworks (HIPAA, GxP) and clinical data standards (OMOP, CDISC, FHIR).
• Hands-on experience with Apache Iceberg, Spark, Databricks, Snowflake, Kafka, or equivalent distributed data processing frameworks.
• Experience designing and implementing knowledge graph architectures, ontology models, or semantic data layers that support AI/ML and agentic AI systems.
• Experience with data governance and cataloging tools (e.g., AWS Glue Data Catalog, Collibra, Alation) and data lineage tracking, including designing data access patterns for identity and least-privilege access.
• Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements, resolve access challenges, and convey technical concepts to both technical and business audiences.
• Proficiency in AI-DLC or equivalent AI-accelerated development methodologies, including prompt engineering, mob programming with AI, and validating AI-generated data pipeline code for production deployment in regulated environments.

About the team

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and continue to innovate, serving customers from startups to Global 500 companies. Our team values diverse experiences, curiosity, and connection. We foster inclusion through employee-led affinity groups and company-sponsored events, empowering our people to take pride in what makes them unique. Our inclusive culture fuels innovation, collaboration, and continuous learning.

We prioritize work-life harmony, offering flexibility to support both professional success and personal well-being. Amazon provides mentorship, career growth resources, and a commitment to raising the performance bar, helping you develop into a better-rounded professional.

Pay

• USA, CA, Mountain View: $176,600.00 - $239,000.00 USD annually
• USA, IL, Chicago: $153,600.00 - $207,800.00 USD annually
• USA, MA, Boston: $153,600.00 - $207,800.00 USD annually
• USA, NC, Raleigh: $153,600.00 - $207,800.00 USD annually
• USA, NJ, Jersey City: $169,000.00 - $228,600.00 USD annually
• USA, NY, New York: $169,000.00 - $228,600.00 USD annually
• USA, VA, Arlington: $153,600.00 - $207,800.00 USD annually
• USA, WA, Seattle: $153,600.00 - $207,800.00 USD annually

Benefits

• Comprehensive health insurance (medical, dental, vision, prescription, Basic Life & AD&D, with options for supplemental life plans).
• Employee Assistance Program (EAP) and Mental Health Support.
• Medical Advice Line and Flexible Spending Accounts.
• Adoption and Surrogacy Reimbursement coverage.
• 401(k) matching.
• Paid time off and parental leave.
• Sign-on payments and restricted stock units (RSUs).