The Amazon Web Services Professional Services (ProServe) team is seeking a Delivery Consultant specializing in Data to join our ASW Industries practice. You will be at the center of the most consequential shift in enterprise technology: making organizations truly AI-ready. Every agentic AI system, every foundation model grounded in enterprise knowledge, and every GenAI application that moves from prototype to production depends on the data layer beneath it - and that's what you build.
You will design and implement modern data platforms (lake, lakehouse, mesh), architect data pipelines that transform raw, fragmented data estates into governed, AI-ready assets; and design and implement enterprise RAG architectures, vector stores, semantic ontologies, and knowledge graph architectures that allow foundation models and AI agents to reason accurately, access data securely, and execute autonomously. You will work hands-on inside customer environments with complex data lineage, legacy systems, and ship production-grade data solutions that serve multiple downstream consumers, from ML model training to agentic orchestration layers.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using AWS services. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing and AI transformation initiatives.
This role requires approximately 50% co-location on site with customer, AWS and partner teams within the U.S.
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Key job responsibilities
- 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
BASIC QUALIFICATIONS
- 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
PREFERRED QUALIFICATIONS
- 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
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, FL, Tampa - 153,600.00 - 207,800.00 USD annually
USA, GA, Atlanta - 153,600.00 - 207,800.00 USD annually
USA, IL, Chicago - 153,600.00 - 207,800.00 USD annually
USA, MN, Minneapolis - 153,600.00 - 207,800.00 USD annually
USA, NJ, Jersey City - 169,000.00 - 228,600.00 USD annually
USA, TX, Austin - 153,600.00 - 207,800.00 USD annually
USA, TX, Dallas - 153,600.00 - 207,800.00 USD annually
USA, VA, Arlington - 153,600.00 - 207,800.00 USD annually
USA, VA, Herndon - 153,600.00 - 207,800.00 USD annually
