Job Description

DESCRIPTION

The Amazon Devices organization designs, produces and markets Kindle e-readers, Fire Tablets, Fire TV Streaming Media Players and Echo Speakers, and is constantly looking to innovate on behalf of customers with new devices in existing or new categories or improving the customer experience on existing platforms. The Devices Analytics team provides customer engagement support to the broader organization for Kindle, Fire, and Echo products established and emerging countries, worldwide.

We are looking for an innovative, hands-on and customer-obsessed Data Engineer who can be a strategic partner to the product managers and engineers on the team.

Our projects span multiple organizations and require coordination of experimentation, economic and causal analysis, forecasting, and predictive machine learning tools. You will act as the business-facing subject matter expert for data storage, feature instrumentation, and data privacy, with the responsibility of managing end-to-end execution and delivery across projects.

In this role, you will be a technical expert with massive impact. You work tightly with the research scientist and business intelligence engineers on our team to create the data infrastructure and pipelines to drive our machine learning projects from initial experimentation to production level deployment. Your work will directly impact the success of Amazon's growing Devices business. You will work across diverse science/engineering/business teams. You will work on critical data engineering problems, building unique high quality reliable, accurate, consistent, and architecturally sound data sets that are aligned with our business needs.

Key Performance Areas
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 using SQL and AWS big data technologies
Explore and learn the latest AWS technologies to provide new capabilities and increase efficiency
Collaborate with Data Scientists and Business Intelligence Engineers (BIEs) to recognize and help adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers

BASIC QUALIFICATIONS

3+ years of experience as a Data Engineer or in a similar role
Experience with data modeling, data warehousing, and building ETL pipelines
Experience in SQL
3+ years of industry experience in software development, data engineering, business intelligence, data science, or related field
Data modeling, ETL development, and data warehousing experience
Experience using big data technologies such as Spark, Hive, Redshift, or S3.
Experience in one or more of: Python, R, Bash, or other scripting language
Experience manipulating, processing, and extracting value from datasets
Knowledge of data management fundamentals and data storage principles

PREFERRED QUALIFICATIONS

Masters in computer science, mathematics, statistics, economics, or other quantitative fields.
Experience working with AWS big data technologies (Redshift, S3, EMR)
Demonstrated strength in data modeling, ETL development, and data warehousing
Proven success in communicating with users, other technical teams, and senior management to collect requirements, describe data modeling decisions and data engineering strategy
Experience providing technical leadership and mentoring other engineers for best practices on data engineering
Familiarity with statistical models and data mining algorithms
Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations