Additional Information
Amazon Web Services (AWS) is seeking an experienced Data Engineer to build next generation data products for the Professional Services - Operations Technology - Data Science and Engineering team. This is a unique opportunity to think big, insist on the highest standards, and invent and simplify data products to scale and accelerate our enterprise customers' journey to the cloud. The team builds advanced analytical products including AI/ML and generative AI tools for use by thousands of internal customers.
AWS provides companies of all sizes with an infrastructure web services platform in the cloud. With AWS you can requisition compute power, storage, and many other services - gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading provider for designing and developing applications for the cloud and is growing rapidly with millions of customers in over 190 countries. Many of these customers seek help from AWS Professional Services in their journey to a cloud-based IT operating model.
Do you have deep expertise in the end to end development of large datasets across a variety of platforms? Are you great at designing data systems and redefining best practices with a cloud-based approach to scalability and automation? In this role, you will be responsible for scaling our existing infrastructure, incorporating new data sources, and building robust data pipelines. In partnership with product and business teams, you will work backwards from our business questions to drive scalable solutions. You will be a technical leader owning the architecture of our data platform and influence best practices across multiple teams. Above all, you should be passionate about working with data.
Key job responsibilities
In this role, you will have the opportunity to display and develop your skills in the following areas
- Develop and support ETL pipelines with robust monitoring and alarming
- Develop data models that are optimized and aggregated for business needs
- Develop and optimize data tables using best practices for partitioning, compression, parallelization, etc.
- Build robust and scalable data integration (ETL) pipelines using SQL, Python, and AWS services such as Glue, Lambda, and Step Functions
- Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL/Redshift
- Interface with business customers, gathering requirements, and delivering complete reporting solutions
- Continually improve ongoing reporting and analysis processes and automating or simplifying self-service support for customers
- Explore and learn the latest AWS technologies to provide new capabilities and increase efficiencies
- Work closely with business owners, analysts, and Business Intelligence Engineers to explore new data sources and deliver new data products
A day in the life
You'll be working on an analytics platform spanning a data warehouse and data lake, supporting reporting, advanced analytics, and generative AI for a large global organization. Day to day, you'll build and maintain data pipelines,
optimize queries, and ensure platform reliability. You'll collaborate with data engineers, BI engineers, and data scientists to deliver accurate, timely data. This role goes beyond traditional data engineering - you'll also own CI/CD
pipelines, manage infrastructure as code, and apply best practices for availability and operational excellence. It's a good fit if you're as interested in the platform itself as the data flowing through it.
Amazon Web · Seattle, WA