- 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
- 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 NCRC (Net Cost of Refunds and Concessions) team within Returns & Re-commerce focuses on ways we can preserve and create customer value while increasing the velocity of Amazon's cost flywheel.
We are constantly innovating to create long-term value at Amazon by investing in the future and focusing on the planet, not just on the bottom line. WW R&R includes business, product, program, operational, and software engineering teams, who together manage the lifecycle of returned and damaged products.
As a Senior Business Intelligence Engineer (Sr. BIE) on the NCRC team within Amazon Returns and Re-commerce, you will be a part of the Science and Analytics team collaborating with a group of Analysts, Economists, PMs and other Engineers. You will have an opportunity to participate and innovate across the engineering landscape, starting from ingestion, storage, processing and reporting. You will build complex data solutions that integrate with cross-organizational systems, enabling our team to scale and build self-serve BI tools. You will partner closely with analysts and economists in the pursuit of investigative data. You will participate in business reviews and new-initiatives. You should be able to identify and help close gaps in the information available, as well as predict up-and-coming -needs when participating in discussions about new products or features.
A successful Sr. BIE will be highly collaborative and organized, capable of prioritizing multiple deliverables and effectively communicate progress and blockers. You should feel comfortable working across multiple systems and AWS technologies, and be capable of participating in and understanding how multiple systems communicate information to one-another.
We are a new team at Amazon and this is a great opportunity to be on the leading edge. Come join us and innovate with the Amazon NCRC team!
Key job responsibilities
-Owning the design, development and maintenance of scalable data solutions for ongoing metrics, reports, analyses, dashboards, etc. to support analytical and business needs.
- Recognize and adopt best practices in reporting and analysis: data integrity, design, analysis, validation, and documentation.
- Use analytical and statistical rigor to answer business questions and drive business decisions.
- Find and create ways to measure the customer experience to drive business outcomes.
- Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.
- Write queries and output efficiently, and have in-depth knowledge of the data available in area of expertise. Pull the data needed with standard query syntax; periodically identify more advanced methods of query optimization. Convert data to make it analysis-ready.
- Troubleshoot operational data-quality issues.
- Review and audit existing ETL jobs and queries.
- Recommending improvements to back-end data sources for increased accuracy and simplicity.
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