Amazon.com Services LLC
Posted Nov 2, 2026
Data Engineer, Advertising Demand Enablement & Product Ops (DEPO)
Midtown · Onsite · Mid · $145.3K–$196.6K
Help moving to NYC
Visa sponsorship likely
Based on 19 NYC H-1B filings for related roles (Data Scientist II, SENIOR MANAGER, DATA ENGINEERING) at Amazon.com Services LLC, Oct 2025–Jun 2026. This is historical evidence, not a promise of sponsorship.
Relocation assistance not stated
Relocation assistance is not stated in this posting.
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Pay
Posted$145,300–$196,600 / year
USA, NY, New York - 145,300.00 - 196,600.00 USD annually
H-1B record$170K Company-wide NYC H-1B median offered wage at Amazon.com Services LLC: $169,761 (819 filings, Oct 2025–Jun 2026). Not specific to this role.
About the role
Are you passionate about building data infrastructure that delivers real business value at massive scale? As a Data Engineer at Amazon, you will design, build, and optimize data pipelines and architectures that transform raw data into actionable insights. You will work alongside software engineers, data scientists, analysts, and business stakeholders to create reliable, performant data solutions that power critical decision-making. This is an opportunity to tackle complex data challenges, shape how information flows across systems, and directly influence outcomes through the quality and accessibility of the data products you deliver.
Key job responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines and data infrastructure, applying best practices in data quality, lineage tracking, and pipeline monitoring to ensure reliable and performant data delivery.
- Create coherent logical and physical data models that accurately represent business requirements, ensure data integrity and consistency, and drive efficient storage and retrieval across relational and distributed systems.
- Develop and optimize SQL queries and scripts to extract, transform, and manipulate large-scale datasets, leveraging distributed data processing frameworks to handle high-volume workloads efficiently.
- Collaborate with analysts, scientists, software engineers, and business stakeholders to translate requirements into well-architected data solutions, balancing customer needs with long-term technical sustainability.
- Identify opportunities to improve existing data processes — including automating manual operations, enhancing data discoverability, and applying generative AI tools where appropriate to augment productivity and data product quality.
A day in the life
You will start your day reviewing pipeline health and data quality metrics, then shift into building or refining ETL workflows that serve downstream analytics and machine learning use cases. You might pair with a data scientist to design a new feature dataset, join a design review to evaluate a proposed architecture change, or mentor a teammate on data modeling patterns. You will regularly engage in code reviews, contribute to team planning, and collaborate across functions to keep data solutions aligned with evolving business priorities.
About the team
Our team is committed to making data accessible, reliable, and valuable across Amazon Ads. We build the foundational data infrastructure that enables analysts, scientists, and engineers to make informed decisions at scale. We operate in a collaborative environment where engineers take meaningful ownership of their domains and contribute to shared standards that raise the bar for everyone. If you are excited about solving complex data problems, working with curious and motivated colleagues, and growing your technical impact, we would love to hear from you.
- 4+ years of data engineering experience
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam
- Knowledge of distributed systems as it pertains to data storage and computing
- Bachelor's degree or foreign equivalent in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience with and deep understanding of advertising technologies (i.e., ad server, DSP)
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, NY, New York - 145,300.00 - 196,600.00 USD annually
USA, WA, SEATTLE - 132,100.00 - 178,800.00 USD annually
Key job responsibilities
- Design, build, and maintain scalable ETL/ELT pipelines and data infrastructure, applying best practices in data quality, lineage tracking, and pipeline monitoring to ensure reliable and performant data delivery.
- Create coherent logical and physical data models that accurately represent business requirements, ensure data integrity and consistency, and drive efficient storage and retrieval across relational and distributed systems.
- Develop and optimize SQL queries and scripts to extract, transform, and manipulate large-scale datasets, leveraging distributed data processing frameworks to handle high-volume workloads efficiently.
- Collaborate with analysts, scientists, software engineers, and business stakeholders to translate requirements into well-architected data solutions, balancing customer needs with long-term technical sustainability.
- Identify opportunities to improve existing data processes — including automating manual operations, enhancing data discoverability, and applying generative AI tools where appropriate to augment productivity and data product quality.
A day in the life
You will start your day reviewing pipeline health and data quality metrics, then shift into building or refining ETL workflows that serve downstream analytics and machine learning use cases. You might pair with a data scientist to design a new feature dataset, join a design review to evaluate a proposed architecture change, or mentor a teammate on data modeling patterns. You will regularly engage in code reviews, contribute to team planning, and collaborate across functions to keep data solutions aligned with evolving business priorities.
About the team
Our team is committed to making data accessible, reliable, and valuable across Amazon Ads. We build the foundational data infrastructure that enables analysts, scientists, and engineers to make informed decisions at scale. We operate in a collaborative environment where engineers take meaningful ownership of their domains and contribute to shared standards that raise the bar for everyone. If you are excited about solving complex data problems, working with curious and motivated colleagues, and growing your technical impact, we would love to hear from you.
- 4+ years of data engineering experience
- Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
- Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
- Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam
- Knowledge of distributed systems as it pertains to data storage and computing
- Bachelor's degree or foreign equivalent in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience with and deep understanding of advertising technologies (i.e., ad server, DSP)
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, WA, SEATTLE - 132,100.00 - 178,800.00 USD annually