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. 10044

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, 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 environmentsPreferred Qualifications
AWS certifications in Data Analytics or Machine Learning Specialty preferred
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 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 Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants:

Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company's reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner. The 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. Amazon also offers 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. Learn more about our benefits at https://amazon.jobs/en/benefits . 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.

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