Our mission: To be Earth's most customer-centric company.
Amazon WorkDocs is a cloud based document storage and sharing service with strong administrative controls and feedback capabilities. WorkDocs is more than just the home for user files – it aims at being the simple, secure and cheap cloud based document management service. It also aims to be home for all the conversations, collaboration and activity surrounding user/team/organization documents.
To enable the vision and asks from our customers, we are looking for strong data engineerswith a proven track record of solving challenging technical problems and creating great products for end users. This is an opportunity to be part of a start-up team for a new AWS business that promises to go big.
The ideal candidate will have an exceptional design, and coding skills along with strong technical acumen. He/She will be will be a catalyst for change by working with the various product managers and principal engineers to code and design flexible and scalable solutions, and work on some of the most complex challenges . If you are passionate about delighting business users with great and compelling cloud based solutions, then we would like to talk to you.
In this role, you will be a technical expert with massive impact. You work tightly with engineers and Product Managers engineers on our team to create the data integrations, ETL, pipelines and codebase to drive our innovative dataplatform projects from initial experimentation to production level deployment. Your work will directly impact the success of Amazon’s growing web services business. You will work across diverse engineering and business teams. You will work on critical data engineering problems, building unique high quality reliable, accurate, consistent, and architecturally sound solutions that are aligned with our business needs.
While the majority of our roles are based in the greater Seattle/Bellevue, WA area, by applying to this position your application will be considered for the following locations. This includes California, New York City and Vancouver.
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Key job responsibilities
Design, implement and support 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 other Engineers and Product Managers to recognize and help adopt best practices in data engineering and analytics: data integrity, test design, analysis, validation, and documentation
Help continually improve ongoing data engineering and analytics processes, automating or simplifying self-service support for customers
* Bachelors/Masters in computer science, mathematics, statistics, economics, or other quantitative fields.
5+ years of industry experience in software development, data engineering, business intelligence, data science, or related field
3+ years data modeling, ETL development, and data warehousing experience.
5+ years of experience using big data technologies such as Spark, Hive, Redshift, or S3.
5+ years Experience in one or more of: Python, R or other scripting language.
Knowledge of software engineering best practices across the development life-cycle, including agile methodologies, coding standards, code reviews, source management, build processes, testing, and operations.
Proven track record of successful communication of analytical outcomes through written communication, including an ability to effectively communicate with both business and technical teams.
* Experience working with AWS technologies (Redshift, S3, EMR,SNS,SQS)
Experience with Elasticsearch, Apache Solr, or Apache Lucene
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
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.