Job Description
Amazon Advertising operates at the intersection of e-Commerce and Advertising, offering a range of digital advertising solutions with the goal of helping our customers discover and shop for anything they want to buy.
The Amazon Advertising business is growing at a fast pace and this team?s mission is to apply science and technology to accelerate that growth through best-in-class solutions. We are part of the Sales Recommendations & Insights team within Sales & Partner Enablement (SPE) to deliver solutions to improve Amazon Advertising Sales team effectiveness worldwide. We are building products for Amazon Advertising front line sales team. Our mission is to minimize the effort required for our Sales team to identify opportunities and recommendations to help their brands grow on Amazon.
The team is looking for motivated Business Intelligent Engineers. In this role you will be responsible for and will build the foundational data pipelines and data tables, analyze large data sets, prove and disprove hypothesis, automate solutions and build self-service dashboards and reports. This person consistently employs high judgment and makes data-driven decisions, leading by example and influencing the team to do the same.
Key job responsibilities
Analyze and solve business problems at their root, stepping back to understand the broader context.
Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations that will shape the future of the Amazon Business.
Develop end-to-end self-service BI solutions to support decision making for the key stakeholder.
Train business stakeholders to use the BI tools and to be autonomous in data analysis.
Research and implement novel approaches to enhance existing technical and business processes to improve customers and stakeholders experience.
Basic Qualifications
5+ 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.
The Amazon Advertising business is growing at a fast pace and this team?s mission is to apply science and technology to accelerate that growth through best-in-class solutions. We are part of the Sales Recommendations & Insights team within Sales & Partner Enablement (SPE) to deliver solutions to improve Amazon Advertising Sales team effectiveness worldwide. We are building products for Amazon Advertising front line sales team. Our mission is to minimize the effort required for our Sales team to identify opportunities and recommendations to help their brands grow on Amazon.
The team is looking for motivated Business Intelligent Engineers. In this role you will be responsible for and will build the foundational data pipelines and data tables, analyze large data sets, prove and disprove hypothesis, automate solutions and build self-service dashboards and reports. This person consistently employs high judgment and makes data-driven decisions, leading by example and influencing the team to do the same.
Key job responsibilities
Analyze and solve business problems at their root, stepping back to understand the broader context.
Identify, develop, manage, and execute analyses to uncover areas of opportunity and present written business recommendations that will shape the future of the Amazon Business.
Develop end-to-end self-service BI solutions to support decision making for the key stakeholder.
Train business stakeholders to use the BI tools and to be autonomous in data analysis.
Research and implement novel approaches to enhance existing technical and business processes to improve customers and stakeholders experience.
Basic Qualifications
5+ 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.
Key skill Required
- SQL
- Python
- AWS
- Automation
- Data Analysis
- Sales
- Advertising
- Advertising Sales
- Analysis
- Data Mining
- Data Pipelines
- Data Science
- Decision Making
- Design
- E-commerce
- Effectiveness
- Inclusive
- Leadership
- Learning
- Machine Learning
- Mining
- Onboarding
- Orientation
- Research
- Science
- Statistical Analysis
- Team Effectiveness
