A

Amazon

Sells products online and rents cloud computing

Delivery Consultant - Multiple Teams

Data EngineeringConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • At least 5 years of cloud architecture and solution implementation experience.
  • A bachelor's degree, or at least 7 years of professional or military experience.
  • At least 5 years of experience in data engineering, data architecture, and/or data platform development, including hands-on implementation of production data pipelines.
  • Experience with modern data platform design patterns, including data lakes, lakehouses, data mesh, 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 architecting and engineering ontologies and knowledge graphs in enterprise environments.

Responsibilities

  • Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures in enterprise healthcare and life sciences environments, integrating with legacy systems and existing data governance frameworks.
  • Build data products for downstream applications and use cases, from AI/ML model training to agentic AI systems, ensuring data quality, lineage, and reliability at scale.
  • Operate autonomously within delivery engagements, making decisions on data modeling, pipeline design, and architecture without waiting for complete specifications or constant oversight.
  • Navigate data access, security, and privacy requirements in pharmaceutical and healthcare settings, including GxP compliance constraints, HIPAA, and regulatory data governance frameworks.
  • Architect contextual knowledge layers, including ontologies and knowledge graphs using AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions, to help AI agents reason accurately and act autonomously in regulated environments.
  • Collaborate with customer IT, business, and partner teams to secure data access, understand source-system context, and resolve data quality challenges.
  • Deliver iteratively when requirements are ambiguous, translating incomplete business needs into well-architected data solutions that can evolve as customer understanding matures.
  • Apply AI-accelerated Development Life Cycle (AI-DLC) methodologies to redesign data workflows for AI-native delivery at greater scale and pace.

Desired Qualifications

  • AWS certifications in Data Analytics or Machine Learning Specialty.
  • Experience in healthcare and life sciences, including familiarity with HIPAA and GxP compliance and security frameworks and clinical data standards such as OMOP, CDISC, and FHIR.
  • Hands-on experience with Apache Iceberg, Spark, Databricks, Snowflake, Kafka, or equivalent distributed data processing frameworks.
  • Experience designing and implementing knowledge graph architectures, ontology models, or semantic data layers supporting AI/ML and agentic AI systems.
  • Experience with data governance and cataloging tools such as AWS Glue Data Catalog, Collibra, and Alation; data lineage tracking; and designing data access patterns supporting identity and least-privilege access.
  • Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements and resolve access challenges, and explaining technical concepts to technical and business audiences.
  • Proficiency in AI-DLC or equivalent AI-accelerated development methodologies, including prompt engineering as a development discipline, mob programming with AI, and validating AI-generated data pipeline code for production deployment in regulated environments.

About the Company

Amazon

Sells products online and rents cloud computing

Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.

Company size
10,001+
Company stage
IPO
Headquarters
Seattle, WA
Founded
1994

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