Delivery Consultant - Data , Professional Services, AWS Industries

Amazon Web Services (AWS); Seattle (WA); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Amazon Web Services (AWS) Professional Services Delivery Consultant in Data joins the Industries practice to architect and implement modern data platforms and governance frameworks. You will build data pipelines, lake/lakehouse patterns, and enterprise RAG knowledge layers to enable AI-ready assets across customer environments.

You will work hands-on in customer environments, with approximately 50% co-location on site in the United States, collaborating with AWS, partner teams, and customer IT

Qualifications

• Experience designing and implementing data pipelines in enterprise environments.
• Hands-on with AWS data services and data governance considerations.
• Ability to work with regulated industries and security requirements.

Responsibilities

• Design and implement production-grade data pipelines, data lakes, and lakehouses.
• Build data products serving downstream applications from AI/ML training to agentic systems.
• Operate autonomously in delivery engagements with evolving requirements.
• Navigate data access, security, and privacy in regulated environments.
• Develop contextual knowledge layers using AWS Bedrock and knowledge graphs.
• Collaborate across teams to secure data access and resolve quality issues.
• Deliver iteratively to convert ambiguous needs into scalable data solutions.
• Apply AI-DLC methodologies to rework data workflows for AI-native scale.

Skills

Data engineering

Cloud architecture

Python

SQL

Spark/ETL

Education

Bachelor's degree in a technical field

AWS Professional level certification

Tools

S3

Glue

Iceberg

Lake Formation

Redshift

Bedrock Knowledge Bases

Ontology/Knowledge Graph

Job description

Description

The Amazon Web Services Professional Services (ProServe) team is seeking a Delivery Consultant specializing in Data to join our AWS 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 within regulated environments. You will work hands-on inside customer environments with complex data lineage, legacy systems, and Build production-grade data solution 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.

Key Job Responsibilities

• Design and implement production-grade data pipelines, data lakes, and lakehouses within an enterprise environment, contributing to data mesh patterns and 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 sound 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 in a regulated Telco environment
• Help build contextual knowledge layers — 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
• 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, redesigning data workflows to become AI-native for accelerated scale and pace

Experience

• Hands-on data engineering (SQL, Spark/ETL, Python) and the AWS data stack (S3, Glue, Iceberg/Lake Formation, Redshift where warranted)
• Building data lakes/lakehouses in enterprise environments
• Working with data governance, security, and privacy
• Telco customer experience
• Plus: exposure to AI/ML data enablement, Amazon Bedrock Knowledge Bases, and ontology/knowledge-graph concepts is a strong plus

About The Team

ABOUT AWS:

Diverse Experiences

Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Inclusive Team Culture

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship and Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Basic Qualifications

• 3+ years of cloud architecture and solution implementation experience
• Knowledge of the primary aws services (ec2, elb, rds, route53 & s3)
• Experience implementing AWS services in a variety of distributed computing environments

Preferred Qualifications

• 5+ years of IT implementation experience
• degree in advanced technology, or AWS Professional level certification
• Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
• Knowledge of security and compliance standards including HIPAA and GDPR