Data Engineer, Advertising Demand Enablement & Product Ops (DEPO)
Posted Updated
Description
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.
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.