Business Intelligence Engineer, Flex Analytics

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The Amazon Flex Analytics team is building the global data platform that powers Amazon Flex worldwide. We’re working hard, having fun, and making history!

The Flex Analytics team’s mission is to empower the Worldwide Flex organization with accurate, timely data and actionable insights that enables data-driven decision making at any level. Our goal to achieve this mission is to mature our service offerings to match the needs of our various customers. For our information consumers on the business and product teams we aim to provide insightful analyses that answer the ‘So what do we do about it?’ questions and not just the ‘What happened?’ questions. We provide access to core metrics and datasets via self-service tools that allow our customers to perform ad-hoc or exploratory analyses without the need for a BI developer. For our power users, which includes our science and tech teams, we serve as trusted partners and provide data engineering expertise and access to data at scale to support their business needs.

Key job responsibilities
We are making a fundamental shift from a team that answers questions to an AI-native decision intelligence platform that proactively detects problems, diagnoses root causes, and recommends actions — with or without human prompt. For this, we are hiring a Business Intelligence Engineer (BIE) to help us accelerate our development efforts. This person will build new business intelligence solutions end-to-end. The ideal candidate will be passionate about working with big data sets and have the expertise to utilize these data sets to derive insights, answer business questions and drive growth.

Key job responsibilities
The primary responsibilities of this role include:
Design, develop and maintain scaled, automated, user-friendly systems, reports and dashboards that support our analytical and business needs for forecasting and pricing.
Use analytical and statistical rigor to solve complex problems and drive business decisions that help us achieve our strategic goals.
Write high quality SQL code to retrieve and analyze data from database tables (primarily Redshift) and the data lake.
Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.

In addition to leading the design, development, and management of our analytical tools and reporting, we will also look to this person to provide thought leadership and business analysis support as needed. The successful candidate will demonstrate strong business acumen, experience in developing reporting and analytical infrastructures, strong communication skills, an ability to work effectively with cross-functional teams, and an ability to work in a fast paced and ever-changing environment.

Basic qualifications

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 2+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience
- Bachelor's degree or above in business administration, finance, economics, computer science, data science, engineering, or other related field
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience using SQL (Structured Query Language) to pull data from a database or data warehouse
- Experience using Python scripting to process data for modeling

Preferred qualifications

- Master's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Knowledge of Microsoft Excel at an advanced level, including: pivot tables, macros, index/match, vlookup, VBA, data links, etc.
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business

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