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. Your work will enable AI agents to reason accurately, access data securely, and execute autonomously within regulated environments like HCLS.

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. This role requires approximately 50% co-location on-site with customer, AWS, and partner teams within the U.S.

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 using AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions to equip AI agents with reasoning guardrails.
• Collaborate across organizational boundaries to secure data access, resolve data quality challenges, and align 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 AI-native 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 using services such as Amazon SageMaker Lakehouse, SageMaker Unified Studio, Amazon S3 Tables, Amazon Redshift, and zero-ETL integrations.
• Experience with architecting and engineering ontologies and knowledge graphs in enterprise environments.

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.
• 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. AWS values diverse experiences and encourages candidates from non-traditional career paths to apply.

We prioritize work-life harmony, offering flexibility to support both professional success and personal well-being. Our inclusive culture fosters collaboration through employee-led affinity groups and inclusion events, while mentorship and career growth resources help you develop as a 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

Compensation includes sign-on payments, restricted stock units (RSUs), and comprehensive benefits such as health insurance, 401(k) matching, paid time off, and parental leave. Learn more at amazon.jobs/en/benefits.