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.

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

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
Experience with architecting and engineering ontologies and knowledge graphs in enterprise environments
Experience with data governance and cataloging tools (e.g., AWS Glue Data Catalog, Collibra, Alation) and data lineage tracking and designing data access patterns that support identity and least-priviledge access
Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements and resolve access challenges and conveying technical concepts to both technical and business audiences.
Proficiency in AI-DLC or equivalent AI-accelerated development methodologies — including prompt engineering as a development discipline, mob programming with AI, and experience validating AI-generated data pipeline code for production deployment in regulated environments

Qualifications

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
Experience with architecting and engineering ontologies and knowledge graphs in enterprise environments
Experience with data governance and cataloging tools (e.g., AWS Glue Data Catalog, Collibra, Alation) and data lineage tracking and designing data access patterns that support identity and least-priviledge access
Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements and resolve access challenges and conveying technical concepts to both technical and business audiences.
Proficiency in AI-DLC or equivalent AI-accelerated development methodologies — including prompt engineering as a development discipline, mob programming with AI, and experience validating AI-generated data pipeline code for production deployment in regulated environments

Skills

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 and designing data access patterns that support identity and least-priviledge access
Collaboration 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
Delivery iteratively when requirements are ambiguous, translating incomplete business needs into well-architected data solutions that can evolve as customer understanding matures
Application of AI-DLC or equivalent AI-accelerated development methodologies — including prompt engineering as a development discipline, mob programming with AI, and experience validating AI-generated data pipeline code for production deployment in regulated environments

Benefits

Comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave

Pay

Base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location.

Schedule

Approximately 50% co-location on site with customer, AWS and partner teams within the U.S.