Data Engineer


Job Overview


Amazon Web Services (AWS) is a dynamic and rapidly growing business within Amazon, with over a million active customers.

Elastic File System (EFS) is the newest AWS storage service poised to grow to hundreds of thousands of servers, exabytes of storage, and trillions of files; and we’re just getting started. EFS is a unique service that provides low-latency, shared file system access to tens of thousands of EC2 instances and on-premises datacenter applications. It is a distributed, highly-available, durable file storage service that is fully elastic, growing and shrinking as required. If you have the files, we have the storage! For more information on EFS and to understand its customer benefits, please visit

Embark on a journey with us to build a distributed file storage service that can scale without limits. We need your passion, innovative ideas, and creativity to help take the service to new heights. This is an opportunity to shape the future of EFS. Our mission is to transform the way the world uses file storage. Listen to how we are enabling our customers to change the world – .

Primary responsibilities will be
· Design, implement and support an analytical data infrastructure providing ad-hoc access to large datasets and computing power.
· 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.
· Creation and support of real-time data pipelines built on AWS technologies including Glue, Redshift/Spectrum, Kinesis, EMR and Athena
· Continual research of the latest big data and visualization technologies to provide new capabilities and increase efficiency
· Working closely with team members to drive real-time model implementations for monitoring and alerting of risk systems.
· Collaborate with other tech teams to implement advanced analytics algorithms that exploit our rich datasets for statistical analysis, prediction, clustering and machine learning
· Help continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers


· 1+ 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
· 2+ years of industry experience in software development, data engineering, business intelligence, data science, or related field with a track record of manipulating, processing, and extracting value from large datasets
· Demonstrated strength in data modeling, ETL development, and data warehousing
· Experience using big data technologies (Hadoop, Hive, Hbase, Spark etc.)
· Knowledge of data management fundamentals and data storage principles
· Experience using business intelligence reporting tools (Tableau, Business Objects, Cognos etc.)


· Degree/Diploma in computer science, engineering, mathematics, or a related technical discipline
· Experience working with AWS big data technologies (Redshift, S3, EMR)
· Experience building/operating highly available, distributed systems of data extraction, ingestion, and processing of large data sets
· Experience working with distributed systems as it pertains to data storage and computing
· Knowledge of software engineering best practices across the development lifecycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations

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