Business Intelligence Engineer II, IES Shopping

Full Job Description

Smart Shopping Experience (SSE) has a vision to embed a data culture deeply in our IES Shopping Experience organization, fostering invention through insights, and building a robust data architecture to support business needs. We spin the insights flywheel by growing a pool of bar-raisers and diverse data professionals, which empowers us to continuously enhance our data capabilities, holistically covering disciplines of Data Engineering, Business Intelligence, Analytics, and Machine Learning.

We are looking for a candidate that demonstrated success working cross-functionally across internal and external teams. This candidate must have a track record of churning out actionable insights and make data backed recommendations that directly impact organizational strategic decisions and priorities. Being able to thrive in an ambiguous, fast-moving environment and prioritizing work is essential, as is a mind for innovation and learning through new technologies. This role provides an opportunity to develop original ideas, approaches, and solutions in a competitive and ever-changing business climate.

Key job responsibilities Key job responsibilities

Conduct deep dive analyses of business problem statements and formulate conclusions and recommendations to leadership Share written recommendations and insights for key stakeholders that will help shape organizational strategic decisions and priorities Contribute to the design, implementation, and delivery of BI solutions for complex and ambiguous problems Simplify and automate reporting, audits, and other data-driven activities Partner with other BIEs to enhance data infrastructure, data availability, and broad access to customer insights Develop and drive best practices in data integrity, consistency, analysis, validations, and documentation Learn new technology and techniques to meaningfully support internal stakeholders and process innovation

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, or 2+ years of Amazon RME (BB/3P) Full Time Exempt 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 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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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, or 2+ years of Amazon RME (BB/3P) Full Time Exempt 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 using SQL (Structured Query Language) to pull data from a database or data warehouse Experience using Python scripting to process data for modeling