Seattle, Washington, USA
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The AWS Capacity Forecasting and Planning team engages with all AWS service teams to build the world's largest Cloud infrastructure. Come make history!
Our team forecasts demand and recommends hardware ordering for the largest AWS service teams. As part of infrastructure and planning, we forecast customer demand, build inventory replenishment systems, and drive utilization improvement for all AWS services.
As a member of the team you will help manage the data inputs and forecast outputs for:
- Enhancing and testing statistical models used to generate forecasts for all AWS services.
- Capacity planning systems that optimize service availability and infrastructure costs.
- World-class forecasting systems that process billions of time series each week.
- Inventory replenishment systems developed for each AWS service.
What you will learn:
- How to incorporate tested research results into modern software systems that improve the way AWS operates.
- Inventory management and supply chain management for the Cloud.
- The internal workings of all AWS services.
- The data that supports growth of the world’s largest Cloud, solving challenging problems on a daily basis.
- Leveraging AWS technologies such as Lambda, Glue, and Kinesis to craft ETL solutions.
You will work directly with senior research scientists, a large software development team, and owners of all major AWS services. This role requires an individual with excellent analytical abilities, deep knowledge of data engineering principles and business intelligence, as well as a passion for problem-solving. Ideally, you are comfortable with ambiguity and accessing and working with data from multiple sources. You will organize large amounts of data, discover and solve real world problems, and expand our overall metrics infrastructure.
Some of the key responsibilities for this position include: - Work with managers, software developers, and scientists to design and develop data infrastructure to support the growth of AWS.
- Enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into digestible and actionable forms.
- Perform deep-dives to find root causes of variances of key forecasting parameters over a given time period.
- Develop intelligent, insightful self-reporting tools.
Database, SQL, Data, Data Engineer, Forecasting, Statistics, Machine Learning, Optimization, Inventory Management, Supply Chain Management, AWS, Cloud, Cloud Computing, EC2, S3, EBS, DynamoDB, CloudFront, Java, C++, object oriented, Java, distributed systems, high availability, scalability, concurrent
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
- B.S. degree in mathematics, statistics, computer science or a similar quantitative field
- 4+ years work experience in relevant field
- Experience in using SQL to analyze data in a database or data warehouse and be able to use a major programming (e.g. Java/C) and/or a scripting language (Perl, Unix shell) to process data for modeling
- prefer 5-10 years experience
- Expert-level knowledge of using SQL to write complex, highly-optimized queries across large volumes of data.
- Understanding of data warehousing and data modeling.
- B.S. degree in math, statistics, computer science or equivalent technical field.
- Ability to separate the data signal from the noise
- Demonstrated ability to frame complex analytical problems, pull data, and extract insights that led to tangible results.
- Experience in gathering requirements and formulating business metrics for reporting.
- Experience with AWS services including S3, Redshift, EMR amd AWS Command line knowledge.
- Experience with Big Data Technologies (EMR , Hadoop, Hive, Hbase, Pig, Spark, etc.)
- Experience working with large data sets in order to extract business insights or build predictive models (data mining, machine learning, regression analysis)
- Good understanding of the cloud industry.
- 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 salary survey at salaries.ai-jobs.net
Tags: AWS Big Data Business Intelligence Computer Science Data Mining Data Warehousing Distributed Systems DynamoDB EC2 Engineering ETL Hadoop Kinesis Lambda Machine Learning Mathematics Perl Redshift Research Spark SQL Statistics Testing
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