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

Amazon Ads is hiring a Data Engineer to design, build, and optimize scalable data pipelines and architectures that convert raw inputs into decision-ready insights. In this onsite role in New York, you will work closely with engineering, data science, analytics, and business stakeholders to deliver reliable, high-performing data solutions at large scale.

Responsibilities

• Design, build, and maintain scalable ETL/ELT pipelines and data infrastructure, applying data quality practices, lineage tracking, and pipeline monitoring to support dependable and performant delivery.
• Create logical and physical data models that reflect business requirements, while ensuring data integrity and consistency and enabling efficient storage and retrieval across relational and distributed systems.
• Develop and optimize SQL queries and scripts for extraction, transformation, and manipulation of large datasets, using distributed data processing frameworks to support high-volume workloads.
• Partner with analysts, scientists, software engineers, and business stakeholders to translate requirements into well-architected data solutions with both customer impact and long-term technical sustainability in mind.
• Find opportunities to improve existing data processes, including automating manual tasks, improving data discoverability, and applying generative AI tools where appropriate to enhance 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 software development life cycle, including coding standards, software architecture, code reviews, source control management, continuous deployments, testing, and operational excellence.
• Knowledge of batch and streaming data architectures such as Kafka, Kinesis, Flink, Storm, and Beam.
• Knowledge of distributed systems as they relate to data storage and computing.
• Bachelor’s degree or foreign equivalent in computer science, engineering, analytics, mathematics, statistics, IT, or equivalent.

Technologies

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

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 stores, key-value stores, graph databases, and column-family databases.
• Experience with and deep understanding of advertising technologies such as ad servers and DSP.

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 and contribute to team planning.
• Collaborate across functions to keep data solutions aligned with evolving business priorities.

About the Team

The team is committed to making data accessible, reliable, and valuable across Amazon Ads. You will help build foundational data infrastructure that enables analysts, scientists, and engineers to make informed decisions at scale. The environment is collaborative, with meaningful domain ownership and shared standards that raise the bar for the team.

Compensation and Location

Location: New York, NY (onsite). Compensation: USD 145,300 - 196,600 per yearly.

Benefits

• Sign-on payments and restricted stock units (RSUs).
• 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.
• Parental leave.