Data Engineer I, AFT BI Content

Have you ever ordered a product from Amazon and been amazed at how fast it gets to you?

Every day Amazon engineers are relentlessly working to decrease the time between Click to Deliver for your products. The Amazon Fulfillment Technologies (AFT) team owns all of the software and infrastructure which powers Amazon"s world-class fulfillment engine. Our team is building complex, massive data systems to capture data during every step in the automated pipeline and use that data to proactively predict efficiency and cost improvements to deliver the packages fast to our customers.

As an Amazon.com Big Data Engineer you will be working in one of the world"s largest and most complex data warehouse environments. You should be skilled in the architecture of DW solutions for the Enterprise using multiple platforms (RDBMS, Columnar, Cloud). You should have experience in the design, creation, management, and business use of extremely large data-sets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. Above all, you should be passionate about working with huge data sets and someone who loves to bring data-sets together to answer business questions and drive change.

As a Data Engineer in this role, you will develop new data engineering patterns that leverage a new cloud architecture, and will extend or migrate our existing data pipelines to this architecture as needed. You will also be assisting with integrating the Redshift platform as our primary processing platform to create the curated Amazon.com data model for the enterprise to leverage. You will be part of a team that builds the next generation data warehouse platform and to drive the adoption of new technologies and new practices in existing implementations. You will be responsible for designing and implementing the complex ETL pipelines in data warehouse platform and other BI solutions to support the rapidly growing and dynamic business demand for data, and use it to deliver the data as service which will have an immediate influence on day-to-day decision-making at Amazon.com.

Key job responsibilities

• Build and maintain backend data infrastructure for analytical and visualization platforms, ensuring data is clean, fresh, and optimized for downstream consumption
• Translate business problem statements into technical data requirements, partnering with product management and stakeholders to define what data products to build
• Automate and optimize reporting processes to enable self-service analytics at scale, reducing manual effort and improving speed to insight
• Develop measurement frameworks and metrics that quantify deal execution performance and operational health
• Ensure data quality through monitoring, validation, auditing, and documentation of pipelines and data sources
• Leverage AWS services and generative AI to build next-generation data solutions that improve efficiency and unlock new analytical capabilities

A day in the life

You will start your day checking pipeline health dashboards and addressing any overnight failures. You might spend the morning writing SQL to transform raw robotics data into productivity metrics, then pair with a senior engineer in the afternoon to design a new data model. You will participate in code reviews, contribute to on-call rotations, and work with business stakeholders to understand what questions they need data to answer.

About the team

Amazon Fulfillment Technologies (AFT) powers Amazon's global fulfillment network. We invent and deliver software, hardware, and data science solutions that orchestrate processes, robots, machines, and people. We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it.

The AFT Data Engineering team specifically owns the data pipelines and analytical tables that measure fulfillment center performance. Our data powers leadership decision-making from individual site managers to VP-level business reviews.