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 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
Youll 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 youll build and maintain data pipelines
optimize queries and ensure platform reliability. Youll collaborate with data engineers BI engineers and data scientists to deliver accurate timely data. This role goes beyond traditional data engineering youll also own CI/CD
pipelines manage infrastructure as code and apply best practices for availability and operational excellence. Its a good fit if youre 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 hasnt followed a traditional path or includes alternative experiences dont let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating thats 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 theres nothing we cant achieve in the cloud.
Inclusive Team Culture
Here at AWS its 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
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing mentorship and other career-advancing resources here to help you develop into a better-rounded professional.


- 3 years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience
- Bachelors 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)

- 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. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including 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 and parental leave. Learn more about our benefits at VA Arlington - 132100.00 - 178800.00 USD annually
USA WA Seattle - 132100.00 - 178800.00 USD annually