Senior Delivery Consultant – Data , ProServe EMEA

Amazon Switzerland seeks a Senior Delivery Consultant in Geneva to design AI-ready data platforms for Healthcare and Life Sciences clients, focusing on modern architectures and agentic AI integration.

This position sits within the AWS Professional Services Healthcare and Life Sciences practice. The primary objective is to help customers prepare for artificial intelligence by constructing robust data layers that support foundation models, generative AI applications, and agentic systems. The role involves close collaboration with client teams and partners to translate business goals into technical data solutions.

Responsibilities

• Architect and deploy modern data structures such as data lakes, lakehouses, and data mesh environments.
• Build pipelines that convert fragmented raw data into governed, high-quality assets suitable for AI consumption.
• Design enterprise Retrieval-Augmented Generation (RAG) systems, including vector stores, semantic ontologies, and knowledge graphs.
• Implement production-grade data products that support downstream use cases ranging from machine learning training to agentic orchestration.
• Navigate complex regulatory environments, including GxP compliance, while managing data lineage and legacy system integration.
• Develop contextual knowledge layers using AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions.
• Operate autonomously within fast-paced delivery engagements, making independent architectural decisions.
• Collaborate across organizational boundaries to resolve data access issues, understand source contexts, and improve data quality.
• Apply AI-DLC methodologies to redesign data workflows, making them AI-native to accelerate development and scale.
• Iteratively deliver solutions even when business requirements are ambiguous, translating incomplete needs into well-architected outcomes.

Requirements

• At least five years of professional experience in data engineering, data architecture, or data platform development.
• Proven track record of implementing production-level data pipelines.
• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
• Strong understanding of modern data platform design patterns, including zero-ETL approaches, streaming architectures, data lakes, lakehouses, and data mesh.
• Experience in engineering ontologies and knowledge graphs within enterprise settings.

Nice to have

• AWS certifications in Data Analytics or Machine Learning Specialty.
• Background in the healthcare and life sciences sector, with familiarity regarding HIPAA, GxP, and clinical data standards like OMOP, CDISC, and FHIR.
• Hands-on experience with distributed processing frameworks such as Apache Iceberg, Spark, Databricks, Snowflake, or Kafka.
• Experience designing semantic data layers, ontology models, or knowledge graphs that support AI and agentic systems.
• Familiarity with data governance and cataloging tools like AWS Glue Data Catalog, Collibra, or Alation.
• Proficiency in AI-accelerated development methods, including prompt engineering, mob programming with AI, and validating AI-generated code.
• Experience collaborating with business teams, IT, and partners to define data requirements and solve access challenges.

What the company offers

• A flexible working culture designed to support work-life harmony.
• Access to extensive knowledge-sharing opportunities, mentorship, and career-advancing resources.
• Participation in employee-led affinity groups that promote an inclusive environment.

About the company

AWS is the world’s most comprehensive and broadly adopted cloud platform, known for pioneering cloud computing and continuous innovation. The company strives to be Earth’s Best Employer by constantly raising performance standards. AWS values diverse experiences and encourages candidates with non-traditional career paths to apply, fostering a nature of curiosity and continuous learning.

• AWS encourages candidates with non-traditional backgrounds to apply.
• The company fosters a culture of curiosity and continuous learning.
• AWS aims to be Earth’s Best Employer by raising performance bars.
• Employee-led affinity groups support a culture of inclusion.