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# Senior Delivery Consultant - Data , Professional Services, AWS Industries

- **Company:** Amazon.com, Inc.
- **Location:** Minneapolis, NC, United States
- **Experience:** Expert
- **Salary:** $153,600.0 - $207,800.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Data Analysis, Cloud Engineering, Code Review, Databases, Information Engineering, Data Governance, Extract Transform Load (ETL), Data Security, Data Systems, Graph Database, Monitoring of Systems, Machine Learning, Software Engineering, Systems Integration, Datadog, Data Logging, Graphics Processing Unit (GPU), Large Language Models, Generative AI, Data Lakes, Information Technology, Build Process, Functional Programming, Data Delivery, Cloudwatch, Software Coding, Splunk, New Relic (SaaS), Software Version Control, Data Pipelines, Legacy Systems
- **Published:** September 2, 2026
- **Apply:** https://www.amazon.jobs/en/jobs/10524345/senior-delivery-consultant-data-professional-services-aws-industries

## About the Role

5+ years of cloud architecture and solution implementation experience

 - Bachelor's degree, or 7+ years of professional or military experience
 - 5+ years of data engineering experience
 - Experience with data modeling, warehousing and building ETL pipelines
 - Experience building ontologies, taxonomies, and semantic relation frameworks, Bachelor's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field, or experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
 - Bachelor's degree, or 5+ years of solving problems with technology in the Healthcare/Life Sciences Industry experience
 - 5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML (Artificial Intelligence/Machine Learning), GenAI (Generative AI), Analytics, Database, and/or Storage experience
 - Experience with logging and monitoring tools, such as: AWS CloudWatch, Datadog, New Relic and Splunk
 - Experience working with customers, technical teams, and management to collect requirements, describe software product features, and technical designs
 - Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware, or experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations

## Description

Design and implement production-grade data pipelines, data lakes, lakehouses, and data mesh architectures within enterprise environments, integrating with legacy systems and existing data governance frameworks

 - Build data products that serve multiple downstream applications and use cases - from AI/ML model training to agentic AI systems, ensuring data quality, lineage, and reliability at scale

 - Operate with a high degree of autonomy within fast-moving delivery engagements, making judgment calls on data modeling, pipeline design, and architecture without waiting for perfect specifications or constant oversight

 - Navigate complex data access, security, and privacy requirements

 - Architect contextual knowledge layers, including ontologies and knowledge graphs leveraging AWS Context, Amazon Bedrock Knowledge Bases, and custom ontology extensions to equip AI agents with the vocabulary and guardrails to reason accurately and execute autonomously within regulated environments

 - Collaborate across organizational boundaries to secure data access, understand source system context, and resolve data quality challenges with teams across customer IT, business, and partner organizations

 - 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 (AI-accelerated Development Life Cycle) methodologies to data delivery to redesign data workflows to become AI-native for accelerated scale and pace


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