Data Engineer II, Professional Services Strategy & Operation, Analytics & Insights Center (PAIC)

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.

About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

BASIC QUALIFICATIONS

- 3+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience
- Experience with SQL and Python scripting
- Experience in data applications using large scale distributed systems (e.g., EMR, Spark, Elasticsearch, Hadoop, Pig, and Hive)

PREFERRED QUALIFICATIONS

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with database, data warehouse or data lake solutions
- Experience with version control systems and CI/CD pipeline implementation
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience working directly with business stakeholders to translate between data and business needs
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers.