Senior Data Engineer

Seattle, Washington, USA

Applications have closed

Amazon.com

Free shipping on millions of items. Get the best of Shopping and Entertainment with Prime. Enjoy low prices and great deals on the largest selection of everyday essentials and other products, including fashion, home, beauty, electronics, Alexa...

View company page

The AWS Worldwide Revenue Operations (WWRO) Customer Insights & Reporting (CIR) team owns solutions that enable internal AWS users to obsess over customers and make proactive, data-driven
recommendations that position AWS as a strategic business partner in addition to a world-class cloud computing provider.
CIR team is looking for a Sr. Data Engineer to play a key role in building their industry leading Customer Information Analytics Platform. Are you passionate about data and highly scalable data platforms? Do you enjoy building end to end Analytics solutions to help drive business decisions? And if you have experience in building and maintaining highly scalable data warehouses and intuitive data insights, then we need you!


In this role, you will work tightly with other date engineers and business intelligence engineers on our team to create data integrations and ETL pipelines to drive our projects from initial experimentation to production deployment. Your work will directly impact the success of Amazon's growing web services business. You will work across diverse engineering and business teams while solving critical data engineering problems, building unique high quality reliable, accurate, consistent, and architecturally sound solutions that are aligned with our business needs.

Key Responsibilities
· Design, implement and support an analytical data infrastructure
· Managing AWS resources including EC2, EMR, S3, Glue, Redshift, etc.
· Interface with other technology teams to extract, transform, and load data from a wide variety of data sources
· Explore and learn the latest AWS technologies to provide new capabilities and increased efficiency
· Collaborate with other Data Engineers and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
· Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
Location: This role open to these locations: Seattle & Dallas. Relocation offered from within the US to any of these locations.

Basic Qualifications




· Bachelor's degree in Engineering, Computer Science, related technical field, or equivalent experience
· 7+ years of experience in data warehouse technical architectures, infrastructure components, ETL/ ELT and reporting/analytic tools.
· Demonstrated strength in data modeling, ETL development and data warehousing
· 7+ years of experience data modeling concepts
· 5+ years of Python and/or Java development experience



Preferred Qualifications

· Master’s degree in Computer science, I.T or Engineering parallels.
· Experience working with AWS big data technologies (Redshift, S3, EMR
· Experience with AWS services.
· Experience building on AWS using S3, EC2, Redshift, DynamoDB, Lambda, QuickSight, etc.


Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.


Tags: AWS Big Data Business Intelligence Computer Science Data Warehousing DynamoDB EC2 ELT Engineering ETL Lambda Pipelines Python QuickSight Redshift

Perks/benefits: Relocation support

Region: North America
Country: United States
Job stats:  8  1  0
Category: Engineering Jobs

More jobs like this

Explore more AI, ML, Data Science career opportunities

Find even more open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general - ordered by popularity of job title or skills, toolset and products used - below.