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Description

Are you passionate about building GenAI based business insights? Do you want to be a part of a fast-paced, ambiguous environment and contribute to one of the biggest payment platform on globe?

In this role you will be responsible for solving complex and ambiguous data and metric problems. You will use latest AWS provide Data Analytics and GenAI tools to provide business metrics for senior leaders. You should have a track record of end-to-end ownership and successfully delivering results in a fast-paced and dynamic business environment. You should be able to work on complex initiatives, deal with ambiguity. You will be required to work with senior leaders, product managers, program managers and sister data teams to understand metrics like ASR, Bad Debt, PSR etc. You will also need to provide metrics around code development, ticket resolution etc.

Key job responsibilities

As a business intelligence engineer, you will/may:

• Be highly data driven, resourceful, customer-obsessed and team oriented

• Use latest AWS provided data analytics and GenAI tools

• Design, develop, and implement scalable, automated processes for data extraction, processing, and evaluation

• Define data driven approaches and metrics strategy to uncover new insights

• Have a passion for sourcing, manipulating, and visualizing data to tell business stories

• Be able to clearly communicate strategic findings and recommendations

• Translate complex, technical concepts into business terms and vice versa

• Work with engineering and data teams to support the development of tools and dashboards

About the team

Payments ML and Data team in GPTech, Amazon Payments, owns the Data and ML use cases, services, product for core payment platforms. We provide payments data to 550+ clients teams in Amazon and have AI/ML products based on that data impacting annual GMS of more than $100MM.

Basic Qualifications

• 10+ years of professional or military experience

• 5+ years of SQL experience

• Experience programming to extract, transform and clean large (multi-TB) data sets

• Experience with theory and practice of design of experiments and statistical analysis of results

• Experience with AWS technologies

• Experience in scripting for automation (e.g. Python) and advanced SQL skills.

• Experience with theory and practice of information retrieval, data science, machine learning and data mining

Preferred Qualifications

• Experience working directly with business stakeholders to translate between data and business needs

• Experience managing, analyzing and communicating results to senior leadership

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.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $117,300/year in our lowest geographic market up to $202,800/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.