Offers “Amazon”

44 days agoAmazon

Business Intelligence Engineer

  • Seattle (King)
  • Marketing

Job description

DESCRIPTION

Interested in building complex data architectures and applying advanced analytical techniques at a large scale? Curious how we decide to fulfill Customer orders in the most efficient way possible across marketplaces and business programs? Want to be a part of a core team dedicated to building the systems that do this?
Every time an Amazon Customer places an order, the Fulfillment Optimization (FO) Team sets the expectation for when their items arrive, and subsequently finds the optimal solution for where and how they will be fulfilled. The Loadbalancer team plays a key role in this fulfillment process by managing and protecting capacity at our Fulfillment Centers. We serve as the interface between Customer expectations and Amazon's industry leading fulfillment capabilities. We are part of Amazon's Supply Chain Optimization Technology (SCOT) Group that develops and manages systems which optimize inventory acquisition, placement of products, transportation and fulfillment plans to enable delivery to our Customers. See this short video for more info (https://tiny.amazon.com/duw7g663/youtwatc)
The Loadbalancer team seeks a brilliant Business Intelligence Engineer (BIE) to join our team. As a Business Intelligence Engineer, you will be responsible for understanding and mining the large amount of data, build metrics and drive customer adoption and business improvements. You will play a leadership role in our team – the team will look to you for advice on analytical and business issues facing them. You will have a department-wide view of the analytical solutions that you build, and you will consistently think in terms of automating or expanding the results company-wide. You should be a self-starter who knows and loves working with BI tools, and who thrives on implementing creative approaches and dealing with the intricate complexity of large data sets, while partnering with customers to answer key business questions. You are analytical and creative, and you don’t quit.
You will also have the opportunity to display your skills in the following areas:
· Interface with business customers, gathering requirements and delivering complete BI solutions.
· Lead customer utilization research projects to better understand how our customers are using our systems, and how we can continue to optimize them to reduce costs.
· Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL (Redshift, Oracle) and ability to use a major programming and/or scripting language to process data for modeling.
· Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation

Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation.

PREFERRED QUALIFICATIONS

· PhD or Masters degree is a plus
· Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
· Advanced knowledge of Oracle BI tools, MySQL, Linux/UNIX, VBA
· Knowledge of scripting for automation (e.g. Python, Perl, Ruby)
· Demonstrated development and application of predictive statistical procedures in languages such as R, SAS, SPS
· Experience in Supply Chain Operations

Desired profile

BASIC QUALIFICATIONS

· Bachelor's degree in Math/Statistics/Engineering or other equivalent quantitative discipline
· 3+ years in relevant experience as business intelligence engineer, data scientist, software engineer, or equivalent
· 3+ years experience processing large scale datasets, analyzing data to solve business problems and presenting impactful insights to business teams, using SQL, Hadoop, Spark, Hive, EMR, or other Big Data technologies
· Knowledge and direct experience using business intelligence reporting/visualization tools (Tableau, MicroStrategy, SSAS Cubes, OBIEE, Business Objects, Cognos, etc.)
· Strong written and verbal communication skills. The role requires effective communication with colleagues from business, machine learning, and economics backgrounds
· Ability to work cross-functionally, building and maintaining trust with internal stakeholders

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