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Senior Delivery Consultant – Data/ Migration, ProServe EMEA

Amazon· ProServe / AWS Professional Services
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Zurich, GenevaFull-timePosted 2mo ago

About the role

Delivery Consultant specializing in Data within AWS ProServe Healthcare and Life Sciences (HCLS) practice, focusing on designing and implementing data platforms, pipelines, and AI-ready data architectures to support regulated environments and AI applications.

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

Qualifications

  • 5+ years of experience in data engineering, data architecture, and/or data platform development, with hands-on implementation of production data pipelines
  • Bachelor's degree in Computer Science, Engineering, Data Science, related field, or equivalent experience
  • Proficiency 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.
  • Experience with architecting and engineering ontologies and knowledge graphs in enterprise environments

Skills

Required:Data engineeringData architectureOntology and knowledge graphsRegulatory data governance (GxP, HIPAA)
Last updated Oct 25, 2026. Interested? Apply on the company site.

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