Senior Delivery Consultant – Data/ Migration, ProServe EMEA

ppAmazon Web Services Professional Services (ProServe) team seeks a Delivery Consultant specializing in Data for our Healthcare and Life Sciences (HCLS) practice. The role focuses on designing and implementing modern data platforms—lakes, lakehouses, mesh—and building AI‑ready data assets to support foundation models and agentic AI systems in regulated environments. /p h3Key job responsibilities /h3 ul liDesign 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. /li liBuild 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. /li liOperate autonomously in fast‑moving delivery engagements, making judgment calls on data modeling, pipeline design, and architecture without waiting for perfect specifications or constant oversight. /li liNavigate complex data access, security, and privacy requirements unique to pharma and healthcare, including GxP compliance constraints, HIPAA, and regulatory data governance frameworks. /li liArchitect 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. /li liCollaborate 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. /li liDeliver iteratively when requirements are ambiguous, translating incomplete business needs into well‑architected data solutions that can evolve as customer understanding matures. /li liApply AI‑DLC (AI‑accelerated Development Life Cycle) methodologies to data delivery to redesign data workflows to become AI‑native for accelerated scale and pace. /li /ul h3Basic Qualifications /h3 ul li5+ years of experience in data engineering, data architecture, and/or data platform development, with hands‑on implementation of production data pipelines. /li liBachelor's degree in Computer Science, Engineering, Data Science, or related field, or equivalent experience. /li liProficiency in 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. /li liExperience architecting and engineering ontologies and knowledge graphs in enterprise environments. /li /ul h3Preferred Qualifications /h3 ul liAWS certifications in Data Analytics or Machine Learning Specialty preferred. /li liExperience in the healthcare and life sciences industry, including familiarity with compliance and security frameworks (HIPAA, GxP) and clinical data standards (OMOP, CDISC, FHIR). /li liHands‑on experience with Apache Iceberg, Spark, Databricks, Snowflake, Kafka, or equivalent distributed data processing frameworks. /li liExperience designing and implementing knowledge graph architectures, ontology models, or semantic data layers that support AI/ML and agentic AI systems. /li liExperience with data governance and cataloging tools (e.g., AWS Glue Data Catalog, Collibra, Alation) and data lineage tracking and designing access patterns that support identity and least‑privileged access. /li liExperience 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. /li liProficiency 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. /li /ul pAmazon is an equal‑opportunity employer. We make recruiting decisions based on your experience and skills. For more information on how we protect your privacy and the security of your data, please consult our Privacy Notice. /p /p #J-18808-Ljbffr