Senior Delivery Consultant - Data, Professional Services, AWSI, Healthcare and Life Sciences

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.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
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.

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: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, 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.

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Basic Qualifications

- Bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or other related field
- Experience in advanced SQL & ability to write complex queries from scratch from multiple tables
- Knowledge of data engineering pipelines, cloud solutions, ETL management, databases, visualizations and analytical platforms
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions

Preferred Qualifications

- Experience with compliance & security standards including PCI DSS, ISO 27001, HIPAA, and NIST
- 6+ years of solving problems with technology in the Healthcare/Life Sciences Industry experience
- Experience in any Bigdata architecture, or experience in Hive/Spark/Hbase/Yarn and experience in Kafka
- 4+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Experience in clinical data standards (OMOP, CDISC, FHIR)
- 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-privilege 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

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