Data Platform Architect for AI-Enabled Healthcare

Amazon; Genf; Vor Ort; CHF 140.000 - 190.000; Vollzeit

Zusammenfassung

Amazon Web Services (AWS) ProServe Data Delivery Consultant for Healthcare and Life Sciences seeks an experienced data professional to design and implement data platforms, pipelines, and knowledge graphs to power AI-ready enterprise solutions in regulated environments.

You will work hands-on in customer environments, shaping data governance, RAG architectures, and secure data access while collaborating with cross-functional teams to deliver scalable data products.

Qualifikationen

• 5+ years of experience in data engineering, architecture, and/or data platform development.
• Bachelor's degree or equivalent in CS, engineering, or data science.
• Proficiency with data lakes/lakehouses, data mesh, and zero-ETL patterns and streaming architectures.

Aufgaben

• Design production-grade data pipelines, lakes, lakehouses, and data mesh architectures within enterprise HCLS environments.
• Build data products serving ML and AI agents, ensuring data quality and lineage.
• Operate autonomously in fast-moving delivery engagements with minimal oversight.
• Navigate data access, security, and privacy, including HIPAA and GxP constraints.
• Collaborate across teams to secure data access and resolve data challenges.

Kenntnisse

Data engineering

Data architecture

Data pipelines

Cloud data platforms

Ausbildung

Bachelor's degree or higher in CS/Engineering/Data Science or related field

Tools

SageMaker Lakehouse

SageMaker Studio

Amazon S3

Redshift

Apache Spark

Jobbeschreibung

Amazon Web Services (AWS) ProServe Data Delivery Consultant for Healthcare and Life Sciences seeks an experienced data professional to design and implement data platforms, pipelines, and knowledge graphs to power AI-ready enterprise solutions in regulated environments.

You will work hands-on in customer environments, shaping data governance, RAG architectures, and secure data access while collaborating with cross-functional teams to deliver scalable data products.