Data Engineer, Deal Tooling and Insights, Strategic Customer Engagements

Amazon Web Services (AWS); Arlington (VA); On-site; USD 132,000 - 179,000; Full time

Job summary

Amazon Web Services, Inc. is seeking a data engineering professional to design and manage large-scale data systems using cloud-native approaches to scalability and automation.

You will build robust pipelines, integrate new data sources, and deliver reliable data products that support analytics, ML, and AI-powered systems. Collaborate with BI engineers and product teams to address business questions with scalable solutions.

Qualifications

• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field.
• 3+ years of data engineering experience.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling.
• Experience with data modeling, warehousing and building ETL pipelines.

Responsibilities

• Architect and implement scalable, reliable, and secure data pipelines for extraction, transformation, and loading from diverse data sources.
• Manage AWS resources including EC2, Redshift, Glue, S3, SageMaker, App Studio, and Bedrock.
• Deploy infrastructure-as-code using CDK.
• Oversee production operations, including optimizing data delivery, scaling infrastructure, code deployments, bug fixes, and release management.
• Design and implement data structures using best practices in data modeling to support reporting, analysis, and machine learning.
• Build semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access.
• Develop infrastructure for agentic AI systems with multi-agent orchestration.
• Ensure data quality through monitoring, validation, auditing, and documentation of pipelines and data sources.
• Read, write, and debug data processing and orchestration code following best coding standards (e.g., version controlled, code reviewed).

Skills

Data engineering

ETL/ELT

SQL

Data modeling

AWS data services

Data warehousing

Education

Bachelor's degree in Computer Science / Engineering / Information Systems / Mathematics

Tools

AWS Glue

Redshift

S3

CDK

Bedrock

SageMaker

Job description

Description

Do you love building scalable data pipelines and engineering reliable datasets? Are you excited by the opportunity to create foundational data infrastructure that powers decision-making across AWS? Are you excited by the opportunity to create foundational data infrastructure that powers decision-making across AWS? Do you want to work in a fast-paced environment, solving data challenges at the intersection of engineering and business impact?

Description

Do you love building scalable data pipelines and engineering reliable datasets? Are you excited by the opportunity to create foundational data infrastructure that powers decision-making across AWS? Are you excited by the opportunity to create foundational data infrastructure that powers decision-making across AWS? Do you want to work in a fast-paced environment, solving data challenges at the intersection of engineering and business impact?

In this role, you will design and manage large-scale data systems using cloud-native approaches to scalability and automation. You will build robust pipelines, integrate new data sources, and deliver reliable data products that support analytics, machine learning, and AI-powered systems. Working closely with business intelligence engineers and product teams, you will work backwards from business questions to build solutions that meet customer needs. The role will leverage generative AI and AWS services to raise the bar on how the team consumes and acts on data, and to build the next generation of AI-enabled data platforms.

Key job responsibilities

Key Job Responsibilities

• Architect and implement scalable, reliable, and secure data pipelines for extraction, transformation, and loading from diverse data sources
• Manage AWS resources including EC2, Redshift, Glue, S3, SageMaker, App Studio, and Bedrock
• Deploy infrastructure-as-code using CDK
• Oversee production operations, including optimizing data delivery, scaling infrastructure, code deployments, bug fixes, and release management
• Design and implement data structures using best practices in data modeling to support reporting, analysis, and machine learning
• Build semantic layers and knowledge graphs enabling intelligent query routing and context-aware data access
• Develop infrastructure for agentic AI systems with multi-agent orchestration
• Ensure data quality through monitoring, validation, auditing, and documentation of pipelines and data sources
• Read, write, and debug data processing and orchestration code following best coding standards (e.g., version controlled, code reviewed)

Basic Qualifications

• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Information Systems, Mathematics, or a related field
• 3+ years of data engineering experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using each of the following: ETL (Extract, Transform, Load)/ELT (Extract, Load, Transform) processes experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
• Experience with data modeling, warehousing and building ETL pipelines

Preferred Qualifications

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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, NY, New York - 145,300.00 - 196,600.00 USD annually

USA, VA, Arlington - 132,100.00 - 178,800.00 USD annually

USA, WA, Seattle - 132,100.00 - 178,800.00 USD annually

Company

Amazon Web Services, Inc.

Job ID: A10499389