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Data Engineer II, Data Management Team
Amazon
H1B ✓On-sitemid levelPosted April 15, 2026
About the Role
The role involves architecting and implementing scalable data pipelines and infrastructure to support analytics and business operations. You will collaborate with cross-functional teams to build robust data solutions and manage AWS resources to ensure high-performance data delivery.
Requirements
Candidates must have at least 3 years of data engineering experience and 1 year of experience with ETL/ELT processes and OLAP technologies. Proficiency in SQL, Python, and AWS services is required to manage large-scale data structures.
Full Job Description
Amazon Web Services (AWS), World-Wide Public Sector Reporting and Analytics team is seeking a Data Engineer with broad technical skills to help build the infrastructure and tools required to support our Global Sales & Operations Organizations.
In this role, the ideal candidate will be responsible for developing and managing big data systems using advanced data engineering knowledge in the data warehousing space and redefining best practices with a cloud-based approach to scalability and automation. Additionally, you will be responsible for scaling our existing infrastructure, incorporating new data sources, and building robust data pipelines for production level systems. In partnership with machine learning engineers, business intelligence engineers and analysts, you will work backwards from our business questions to build reliable and scalable data solutions to meet the business needs. Finally, this individual will work closely with project management teams to ensure proper guidance, use cases, and documentation is available to our Sales and Operations teams.
Key job responsibilities
Responsibilities include:
- Architect and implement scalable, reliable, and secure data pipelines and infrastructure to support analytics, reporting, and business operations.
- Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for business intelligence analytics.
- Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue
- Implementing data structures using best practices in data modeling to provide on-line reporting and analysis using business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources.
- Evaluating and making decisions around dataset implementations designed and proposed by peer data engineers. Mentor junior data engineers.
- Manage AWS resources including EC2, Redshift, S3, etc. Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency.
- Participating in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance to produce comprehensive, usable dataset documentation and metadata.
About the team
About the team
About AWS
AWS 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.
Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
Mentorship & 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.
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.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. Basic Qualifications: - 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience 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.
USA, VA, Arlington - 132,100.00 - 178,800.00 USD annually
USA, VA, Herndon - 132,100.00 - 178,800.00 USD annually
In this role, the ideal candidate will be responsible for developing and managing big data systems using advanced data engineering knowledge in the data warehousing space and redefining best practices with a cloud-based approach to scalability and automation. Additionally, you will be responsible for scaling our existing infrastructure, incorporating new data sources, and building robust data pipelines for production level systems. In partnership with machine learning engineers, business intelligence engineers and analysts, you will work backwards from our business questions to build reliable and scalable data solutions to meet the business needs. Finally, this individual will work closely with project management teams to ensure proper guidance, use cases, and documentation is available to our Sales and Operations teams.
Key job responsibilities
Responsibilities include:
- Architect and implement scalable, reliable, and secure data pipelines and infrastructure to support analytics, reporting, and business operations.
- Design, develop, implement, test, document, and operate large-scale, high-volume, high-performance data structures for business intelligence analytics.
- Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue
- Implementing data structures using best practices in data modeling to provide on-line reporting and analysis using business intelligence tools and a logical abstraction layer against large, multi-dimensional datasets and multiple sources.
- Evaluating and making decisions around dataset implementations designed and proposed by peer data engineers. Mentor junior data engineers.
- Manage AWS resources including EC2, Redshift, S3, etc. Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency.
- Participating in the full development life cycle, end-to-end, from design, implementation and testing, to documentation, delivery, support, and maintenance to produce comprehensive, usable dataset documentation and metadata.
About the team
About the team
About AWS
AWS 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.
Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
Mentorship & 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.
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.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services. Basic Qualifications: - 3+ years of data engineering experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using OLAP technologies experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience
- 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience 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, VA, Arlington - 132,100.00 - 178,800.00 USD annually
USA, VA, Herndon - 132,100.00 - 178,800.00 USD annually