Senior Delivery Consultant – Data, ProServe EMEA

About the role

The AWS Professional Services (ProServe) team is looking for a Senior Delivery Consultant specializing in Data to join its Healthcare and Life Sciences (HCLS) practice. You will design and implement modern data platforms (lake, lakehouse, mesh), data pipelines and enterprise RAG architectures so that foundation models and AI agents can reason accurately and operate securely in regulated environments. The role works hands-on inside HCLS customer environments with complex data lineage, regulatory overlays (GxP, HIPAA, CDISC) and legacy systems.

Key responsibilities

• Design and implement production-grade data pipelines, data lakes, lakehouses and data mesh architectures in HCLS environments, integrating with legacy systems and existing data governance frameworks.
• Build data products serving downstream applications such as AI/ML model training and agentic AI systems, ensuring data quality, lineage and reliability at scale.
• Work with a high degree of autonomy on data modeling, pipeline design and architecture.
• Handle complex data access, security and privacy requirements, including GxP compliance, HIPAA and regulatory data governance.
• Architect knowledge layers such as ontologies and knowledge graphs using AWS Context, Amazon Bedrock Knowledge Bases and custom ontology extensions.
• Collaborate with customer IT, business and partner teams to resolve data quality and access issues, and deliver iteratively when requirements are ambiguous.
• Apply AI-DLC (AI-accelerated Development Life Cycle) methodologies to redesign data workflows for AI-native delivery.

Required profile

• 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 or a related field, or equivalent experience.
• Experience architecting and engineering ontologies and knowledge graphs in enterprise environments.

Required skills

• Proficiency in data lakes, lakehouses, data mesh and zero-ETL patterns, using Amazon SageMaker Lakehouse, SageMaker Unified Studio, Amazon S3 Tables, Amazon Redshift and zero-ETL integrations.
• Preferred: AWS certifications in Data Analytics or Machine Learning Specialty; healthcare and life sciences experience with HIPAA, GxP, OMOP, CDISC and FHIR.
• Preferred: Apache Iceberg, Spark, Databricks, Snowflake, Kafka, data governance tools (AWS Glue Data Catalog, Collibra, Alation) and knowledge graph architectures.
• Preferred: experience with AI-DLC, prompt engineering as a development discipline and validating AI-generated pipeline code for regulated environments.