Data Engineer, Advertising Demand Enablement & Product Ops (DEPO)

In this role at Amazon Ads, you will help turn raw advertising data into dependable, decision-ready information. You will design, build, and continuously improve scalable data pipelines and architectures, working closely with software engineers, data scientists, analysts, and business stakeholders to deliver data solutions at massive scale. The team focuses on building the foundational infrastructure that supports analytics and machine learning while keeping data accessible, reliable, and valuable.

What you’ll do

• Design, build, and maintain scalable ETL/ELT pipelines and data infrastructure, applying data quality practices, lineage tracking, and pipeline monitoring for reliable and performant delivery.
• Create logical and physical data models that reflect business requirements, supporting data integrity and consistency across relational and distributed systems.
• Develop and optimize SQL queries and scripts to extract, transform, and manipulate large-scale datasets, using distributed processing frameworks to handle high-volume workloads.
• Partner with analysts, scientists, software engineers, and business stakeholders to translate requirements into well-architected solutions, balancing customer needs with long-term technical sustainability.
• Spot opportunities to improve data processes by automating manual work, enhancing data discoverability, and using generative AI tools when appropriate to improve productivity and data product quality.

Requirements

• 4+ years of data engineering experience.
• Experience building and operating highly available, distributed systems for data extraction, ingestion, and processing of large datasets.
• Knowledge of professional software engineering practices across the full 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, including Kafka, Kinesis, Flink, Storm, and Beam.
• Knowledge of distributed systems as it relates to data storage and computing.
• Bachelor’s degree (or foreign equivalent) in computer science, engineering, analytics, mathematics, statistics, IT, or an equivalent field.

Technologies

• ETL/ELT, SQL
• Kafka, Kinesis, Flink, Storm, Beam
• Hadoop, Hive, Spark, EMR

A day in the life

• Review pipeline health and data quality metrics.
• Build or refine ETL workflows that support downstream analytics and machine learning use cases.
• Pair with a data scientist to design a new feature dataset.
• Join design reviews to evaluate architecture changes.
• Mentor teammates on data modeling patterns.
• Participate in code reviews, contribute to team planning, and collaborate across functions to align with evolving business priorities.

About the team

• Focuses on making data accessible, reliable, and valuable across Amazon Ads.
• Builds foundational infrastructure that enables analysts, scientists, and engineers to make informed decisions at scale.
• Operates as a collaborative environment where engineers take meaningful ownership of their domains and contribute to shared standards.

Location and compensation

• Location: New York, NY (onsite)
• Salary: USD 145,300 - 196,600 per year

Benefits

• Sign-on payments and restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, 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
• Parental leave

Preferred qualifications

• Experience with big data technologies such as Hadoop, Hive, Spark, and EMR.
• Experience with non-relational databases or data stores, including object storage, document or key-value stores, graph databases, and column-family databases.
• Experience with and deep understanding of advertising technologies (for example, ad server and DSP).