Are you ready to embark on a thrilling journey in the realm of grocery e-commerce? We're on the lookout for a team member to work on our latest initiative, operating at the forefront of innovation in a dynamic, fast-paced environment. This role demands the agility to navigate analytics landscape across multiple functions seamlessly, the resilience to thrive in a fast paced environment, excitement to handle challenges head-on and excellence in analytical abilities.
As a Business Intelligence Engineer, you'll be deciphering our customers' ever-evolving needs and shaping solutions that elevate their experience with Amazon.
We're seeking someone who thrives on ambiguity, harnessing their first-principle problem-solving skills to drive impactful outcomes. Your ability to cultivate a customer-centric mindset, coupled with a penchant for out-of-the-box thinking, will be instrumental in navigating the complex landscape of our initiative.
Key job responsibilities
Deliver on all analytics requirements across business areas required for launch of the new initiative
Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
Ensure data accuracy by validating data for new and existing tools.
Apply data mining and quantitative analysis to understand ways to improve our content selection for customers
Perform both ad-hoc and strategic data analyses
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Build various data visualizations to tell the story and let the data speak for itself
Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
Build automation to reduce dependencies on manual data pulls etc.
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
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