Key job responsibilities
The ideal candidate will be responsible for identifying and addressing complex business problems and opportunities to improve systems, processes, and tools. They will implement data-driven solutions by designing efficient data models and developing SQL/Python scripts, balancing customer requirements with technological constraints. The successful candidate will set data modeling standards and best practices, while also uncovering insights through statistical analysis. It will be crucial to collaborate closely with business customers, cross-functional teams, and senior leaders to refine requirements, solve problems, and deliver new solutions. When the business requires more granular data access, the candidate will help minimize bottlenecks and advise customers on self-service options. They will also own key metrics, prepare and automate reporting for business reviews, and support executive decision-making with data insights. Essential skills include a bias for action, strong attention to detail, the ability to learn quickly, and the capacity to adapt in a fast-paced, changing environment. The candidate must insist on high standards, make sound decisions, exhibit ownership and accountability, and apply appropriate technologies following best practices.
A day in the life
As a Business Intelligence Engineer supporting the Measurement, Ad Tech, and Data Science (MADS) team, your days will be a dynamic mix of technical and collaborative work. You'll partner with product, finance, and engineering teams to design scalable data solutions powering new advertising innovations. You'll also analyze KPIs, forecast key metrics, and uncover insights to inform critical business decisions - including preparing and automating reporting for regular reviews.
No two days will be the same, but you can expect a steady stream of new challenges, high-visibility projects, and opportunities to make a real impact. If you thrive on solving ambiguous problems and drive data-driven innovation, this role is sure to engage you.
BASIC QUALIFICATIONS
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
PREFERRED QUALIFICATIONS
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $74,100/year in our lowest geographic market up to $165,600/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.