Amazon Now is transforming ultrafast commerce by building systems that deliver a frictionless shopping experience to customers who expect speed, accuracy, and reliability. As a Data Engineer I on the Amazon Now team, you will help design and build the data foundations that power real-time insights, operational excellence, and scalable retail systems used across multiple regions.
In this role, you will work on large-scale data pipelines, automate ingestion and transformation workflows, and improve data quality across diverse sources such as catalog, inventory, search, and customer experience systems. You will collaborate closely with Software Engineers, Applied Scientists, Product Managers, and Business Intelligence Engineers to enable data-driven decisions and high-availability customer experiences.
You will be responsible for building well-structured datasets, optimizing performance, and contributing to the team’s data strategy as we scale to new markets. This is a hands-on role that requires strong problem-solving skills, a commitment to high coding standards, and a passion for working with complex distributed data systems.
Amazon fosters a culture of ownership, curiosity, and continuous learning. As an early-career Data Engineer, you will have opportunities to grow your technical depth, learn from senior engineers, and deliver solutions that directly impact millions of customers. This is an ideal role for someone who wants to build scalable data infrastructure in a fast-paced, customer-obsessed environment.
Key job responsibilities
Key job responsibilities
Design, build, and maintain scalable ETL/ELT pipelines that ingest, transform, and publish high-quality data for analytics and operational use cases.
Develop and optimize data models, schemas, and tables to support reporting, dashboards, and real-time decision-making.
Implement data quality, validation, and auditing mechanisms to ensure accuracy, completeness, and reliability across datasets.
Automate recurring data workflows using AWS services such as Glue, Lambda, EMR, Step Functions, Redshift, DynamoDB, or S3-based architectures.
Build and maintain metrics, dashboards, and self-service datasets that enable stakeholders to understand system health, business performance, and customer experience.
Partner with Software Engineers, Business Intelligence Engineers, Applied Scientists, and Product Managers to understand data requirements and deliver scalable solutions.
Debug and resolve data pipeline issues, ensuring high availability, low latency, and timely data delivery across environments.
Contribute to data governance, documentation, lineage tracking, and best practices for data security and compliance.
Conduct performance tuning of pipelines, queries, and storage layers to improve cost efficiency and throughput.
Support experimentation, root-cause analyses, and launches by providing accurate datasets, analytical tooling, and engineering insights.- 2+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
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