Description

Come join our EU International Technology (INTech) team! We are seeking a customer-focused, analytically and technically skilled Business Intelligence Engineer to deliver insights and analysis across our product portfolio. You will own metrics, dashboarding, and measurement across platforms and products, which help Amazon promote Circular Growth in the EU and beyond. Your work will directly influence Amazon's business and customer promise.

The mission of the INTech Circular Growth team is to become the top destination for customers to get maximum value from items they own, for as long as possible, and with direct environmental/financial benefits. Circular growth is about ensuring that products and their related materials keep creating value in the economy for as long as possible before reaching landfills, hence minimizing the environmental impact directly related to products consumers buy. This is one of the most strategic and complex shifts for the retail industry, which is fueled by EU consumers, but also via compliance mandates, e.g., through environmental badging.

Within Circular Growth, the Repairs team envisions a world where the lifespan of products extends far beyond their initial purchase, fostering sustainability, reducing waste, and enhancing the customer experience. Our vision is to provide best-in-class, cost-effective, and complete repair solutions to Amazon customers (Retail and 3P) for all repairable products, regardless of warranty coverage.

We have a roadmap focused on expanding the Warranty Repairs Program to comply with the regulation changes around repairs in the EU. In March 2023, the EU Commission released the draft for the "Right to Repair" to increase the useful lives of products through repair. It proposes that sellers shall be required to offer repair of a defective item whenever it is cheaper to repair than replace within the legal guarantee period (≥2 years of purchase). To comply with the regulation, (1) we will build self-service repair onboarding experiences for vendors and repair partners, enabling us to scale the existing repair offering to most of warranty cases in focus categories and as much as possible across all remaining repairable categories; (2) we will expand these tools to 3P sellers, thus allowing them to comply as well; (3) we will mitigate gaps in the current customer experience.

Key job responsibilities

In this role, you will:

• Work closely with cross-functional teams, Product, and other Data Engineers across the Retail organization.

• Use analytic tools and languages (notably SQL), and present analytical results and insights using multiple methods, including written summaries and visualization/reporting tools such as Tableau.

• Build scalable solutions/self-serve platforms that will provide data/KPIs to inform business decision-making.

• Investigate data sources across Amazon and expand existing data infrastructure.

• Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations that will help shape the customer engagement, and product roadmap.

• Develop a thorough understanding of customer behavior, competitive product trends, and business drivers to inform decision-making.

• Analyze key insight trends and build models that predict customer behavior, using statistical rigor to simplify and provide thought leadership to influence busniess stakeholders.

• Collaborate with finance and product management as a leader of ongoing analytical support.

• Collect, analyze, and share data to help product teams drive improvement in key business metrics and customer experience.

• Propose and prioritize changes to reporting and create additional metrics and processes based on program changes and customer requirements.

Basic Qualifications

• 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 writing complex SQL queries

• 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

Preferred Qualifications

• 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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