Data Engineer, Hardware Engineering Data Science & Analytics Team

Seattle, Washington, USA

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Job summary
AWS Hardware Engineering is looking for an experienced, innovative Data Engineer to join their Data Science and Analytics team. You will be part of a group of talented engineers and scientists that builds data products and services to turn hardware monitoring data into insights using advanced analytics and machine learning.
As a Data Engineer, you will provide technical leadership, lead data engineering initiatives and build end-to-end analytical solutions that are highly available, scalable, stable, secure, and cost-effective. You strive for simplicity, demonstrate creativity and sound judgement. You deliver data solutions that are customer focused, easy to consume and create business impact.
You are passionate about working with huge datasets and have experience with the organization and curation of data for analytics. You have a strategic and long term view on architecting advanced data eco systems. You are experienced in building efficient and scalable data services and have the ability to integrate data systems with AWS tools and services to support a variety of customer use cases/applications.
In this role, you have the opportunity to:
  • 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.

Basic Qualifications


  • 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 etc.

Preferred Qualifications

  • 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
  • Meets/exceeds Amazon’s leadership principles requirements for this role
  • Meets/exceeds Amazon’s functional/technical depth and complexity for this role


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.

* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Tags: Architecture AWS Big Data Clustering Computer Science Data warehouse ELT Engineering ETL Hadoop Kafka Kinesis Machine Learning Python Redshift Spark SQL Statistics

Perks/benefits: Flex hours

Region: North America
Country: United States
Job stats:  5  0  0

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