Amazon

Business Intel Engineer, Grocery Data Tech Analytics

Austin, TX Seattle, WA
USD 89k - 185k
Oracle R Matlab SQL Python AWS DynamoDB Machine Learning
Description
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 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 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

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $89,600/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. We are looking for a Business Intelligence Engineer to build models and algorithms for procurement, selection, marketing and pricing tools in grocery management.

This role is both creative and data driven – we need someone who can review our current infrastructure, isolate improvement opportunities, help us think big about what to consider in terms of localization, scalability, commodity management, and long term automation. We are looking for someone who will scope and execute analyses to formulate conclusions and recommendations to be presented to senior leadership on business growth opportunities. You will also be responsible for producing insights that will help shape effective strategies to better meet our customers’ needs. You will work closely with internal teams, and partners across the grocery business line and other partner teams in these areas to provide decision support in this rapidly evolving space.

This role requires an individual with excellent statistical and analytical abilities, deep knowledge of business intelligence solutions, and have the ability to work with technology, product development, and business teams. The successful candidate will have 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 to this space.



Key job responsibilities
- Develop new and innovative analyses to inform product strategy and design. This analysis will determine approach and roadmap for key strategic initiatives.
- Analyze relevant business information, and uncover trends and correlations to develop insights that can materially improve our product and strategy decisions.
- Develop clear communications for recommended actions.
- Establish new, scalable, efficient, automated processes for tracking and reporting on progress of initiatives.
- Use machine learning, data mining and statistical techniques to create new, scalable solutions for business problems.

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