A

Amazon

Sells products online and rents cloud computing

Senior Delivery Consultant - Multiple Teams

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in business administration, finance, economics, computer science, data science, engineering, or another related field.
  • Experience with advanced SQL and the ability to write complex queries from scratch across multiple tables.
  • Knowledge of data engineering pipelines, cloud solutions, extract, transform, and load management, databases, visualizations, and analytical platforms.
  • Experience with AWS technologies such as Redshift, S3, AWS Glue, EMR, Kinesis, Firehose, Lambda, and IAM roles and permissions.

Responsibilities

  • Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures in enterprise healthcare and life sciences environments, integrating legacy systems and existing data governance frameworks.
  • Build data products for downstream applications and use cases, from AI and machine learning model training to agentic AI systems, ensuring data quality, lineage, and reliability at scale.
  • Operate autonomously in delivery engagements and make decisions on data modeling, pipeline design, and architecture.
  • Navigate pharma and healthcare data access, security, and privacy requirements, 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 operate within 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-DLC methodologies to data delivery and redesign data workflows to become AI-native.

Desired Qualifications

  • Experience with compliance and security standards including PCI DSS, ISO 27001, HIPAA, and NIST.
  • Six or more years of solving technology problems in the healthcare or life sciences industry.
  • Experience with big data architectures or Hive, Spark, HBase, YARN, and Kafka.
  • Experience with data and AI technologies, including AI and machine learning, generative AI, analytics, databases, or storage.
  • AWS certifications in Data Analytics or Machine Learning Specialty.
  • Experience with clinical data standards such as OMOP, CDISC, and FHIR.
  • Experience with data governance and cataloging tools such as AWS Glue Data Catalog, Collibra, and Alation; data lineage tracking; and designing data access patterns that support identity and least-privilege access.
  • Experience collaborating with customer business teams, IT, and partner organizations to understand data requirements, resolve access challenges, and communicate 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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