Business Intelligence Engineer - SSP Analytics, Seller Success Programs Analytics

Description

Are you looking for a role that allows you to shape the future of how new sellers launch and grow their businesses globally with Amazon? Do you like working in a start-up like environment with the opportunity to have a significant impact from day 1? Do you have an insatiable curiosity about why Amazon global stores operate as they do and how Amazon could optimize its selling partner experience? If so, then keep reading as this could be the role for you.

Over 2MM active sellers in 22 countries (and growing) list their products for sale on the Amazon stores. New sellers are a critical part of Amazon's ecosystem to deliver on our vision of offering the earth's largest selection and lowest prices, and helping them successfully register, onboard, and scale is fundamental to that mission.

As a Business Intelligence Engineer (BIE) on the Seller Success Programs Analytics team, you will be responsible for bringing data to the table, specifically seller anecdotes and business metrics across the new seller journey. The ideal candidate thrives in working in large and complex data warehouse environments, has excellent verbal and written communication skills, is motivated by developing innovative and simplified solutions to solve complex analytical problems and is passionate about working with large data sets and bringing data together to answer business questions and drive change. These analyses and solutions will be fundamental to finding opportunities and creating new programs aimed at accelerating seller registration, onboarding, and growth on Amazon stores.

Key job responsibilities
Engage with leadership and diversified customer groups to understand the needs and recommend business intelligence solutions.
Partner with engineering teams to define the data elements and data structures that the team should leverage to develop critical new seller experience metrics across registration, onboarding, and launch.
Design, implement, and support platforms that provide business teams ad-hoc access to large datasets for self service deep dives (eg: data visualization tools for non-tech business users).
Interface with business customers, gather requirements and deliver complete reporting solutions.
Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
Participate in strategic & tactical planning discussions.
Standardize data and report consumption across all customer groups.
Make recommendations for new metrics, techniques, and strategies to improve seller success and program quality metrics.
Be connected and influential within the Amazon BIE community, and work with data engineering and software development teams to enable the appropriate capture and storage of key data points.

A day in the life
You'll partner with product managers, program leaders, and engineering teams across the new seller journey to turn ambiguous business questions into clear, data-driven answers. A typical day mixes deep-dive analysis on registration, onboarding, and launch funnels; building and maintaining metrics, dashboards, and reports that leaders rely on for weekly and monthly business reviews; and gathering requirements from stakeholders to deliver self-service reporting. You'll dig into large, complex datasets to surface opportunities, size the impact of new programs, and influence the roadmap that helps sellers reach their first milestones faster.

About the team
Seller Success Programs Analytics is the data backbone for Amazon's mission to be the premier destination for new sellers worldwide to launch and grow durable businesses. We measure and improve every step of the new seller journey, from registration and onboarding through to first sale and long-term growth. We operate in a fast-moving, start-up-like environment where analysts have direct impact on strategy and own their metrics end-to-end. We value curiosity, ownership, and simplifying the complex, and we invest in each other's growth.

Basic Qualifications

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 1+ years of SQL, ETL or Oracle experience
- 1+ years of processing large, multi-dimensional datasets from multiple sources experience
- 1+ years of performing statistical analysis experience
- 1+ years of developing automated reporting experience
- 3+ years of in the job offered or a related occupation experience
- 1+ years of using SQL, ETL (Extract, Transform, Load), or Oracle experience
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a 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

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
- Demonstrated experience leveraging generative AI tools to enhance workflow efficiency and productivity, with the ability to craft effective prompts and critically evaluate AI-generated outputs in a professional setting
- Experience identifying opportunities to integrate AI solutions into products and services to drive business value

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.