Business Intelligence Engineer, Amazon Customer Service

DESCRIPTION

Amazon's Customer Service (CS) department is seeking an experienced Business Intelligence Engineer (BIE) to join the team. Customer service is the heart of Amazon; our vision is to be "Earth's most customer-centric company; to build a place where people can come to find and discover anything they might want to buy online."

The successful candidate will be a key member of the Amazon CS Data Analytics Support Hub (DASH). This team supports internal stakeholders (leadership team, project managers, program managers) with reactive analytics requests and pro-actively builds tools to improve department productivity and ease of access to data and analytical resources.

A successful candidate will have a deep knowledge of business intelligence solutions and the ability to work with AWS services, Python programming, project management, and business teams. They will have a passion for data and analytics, be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and entrepreneurial environment, and driven by a desire to innovate Amazon's approach in this space.

Tools used include:

1. SQL (Redshift)
2. AWS Services - S3, Lambda, Athena, Glue, EC2, ECS, Kinesis, CDK
3. Python, Linux
4. ETL tools (internal)
5. Data visualization - QuickSight

Key job responsibilities

1. Design, build, and maintain data pipelines, reporting, analytical & automation tools on AWS.
2. Work with a variety of data sources and large data sets, pull data using efficient query development and provide a holistic and consistent view of the data to facilitate analytical insights.
3. Debug report issues, unblock workflows and communicate with other teams and customers to provide status updates.
4. Automate existing processes where needed.
5. Work with our customers on incoming reactive requests to understand their needs and design reporting, analytics, and data pipeline solutions that will exceed expectations.
6. Pro-actively develop flexible and scalable solutions using AWS services and Amazon internal tools.
7. Stay up-to-date on the latest AWS services and technologies.
8. Ratio of reactive, stakeholder initiated workload vs. proactive, project related workload: 50:50.

BASIC QUALIFICATIONS

• Experience writing complex SQL queries.
• Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience with data visualization using Tableau, Quicksight, or similar tools.
• Experience in the data/BI space.
• Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift.

PREFERRED QUALIFICATIONS

• Experience in data mining, ETL, etc., and using databases in a business environment with large-scale, complex datasets.
• Experience with forecasting and statistical analysis.
• Experience in Statistical Analysis packages such as R, SAS, and Matlab.

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