Data Engineer, HWEng Data Science & Analytics team

$118,900 - $205,600/Yr

Amazon - Seattle, WA

Full-time - Mid Level

Seattle, WA

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Data Engineer role within the AWS Hardware Engineering Data Science and Analytics team focuses on building data products and services that transform hardware monitoring data into actionable insights through advanced analytics and machine learning. The position emphasizes technical leadership, the development of scalable analytical solutions, and collaboration with engineers and scientists to enhance data systems and algorithms.

Responsibilities

• Design, implement and operate large-scale, high-volume, high-performance data structures for analytics and data science.
• Implement data ingestion routines both real-time and batch using best practices in data modeling, ETL/ELT processes by leveraging AWS technologies and big data tools.
• Gather business and functional requirements and translate these requirements into robust, scalable, operable solutions with a flexible and adaptable data architecture.
• Collaborate with engineers to help adopt best practices in data system creation, data integrity, test design, analysis, validation, and documentation.
• Collaborate with scientists to create fast and efficient algorithms that exploit our rich data sets for optimization, statistical analysis, prediction, clustering, and machine learning.
• Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service modeling and production support for customers.

Requirements

• A Bachelor's degree in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering) or equivalent industry experience.
• 3+ years of experience with demonstrated strength in ETL/ELT, data modeling, data warehouse technical architecture, infrastructure components and reporting/analytic tools.
• 3+ years of hands-on experience in writing complex, highly-optimized SQL queries across large data sets.
• 3+ years of experience in scripting languages like Python.

Nice-to-haves

• Experience with AWS services such as Redshift, Glue, S3, EMR, Kinesis and SNS/SQS.
• Experience architecting data lake and cloud data warehouses.
• Experience with big data technologies (Hadoop, Hive, Kafka, Spark, etc.).
• Experience in leading and delivering end-to-end projects.
• AWS certifications or other related professional technical certifications.

Benefits

• Comprehensive medical, financial, and other benefits package.
• Equity and sign-on payments as part of total compensation.