Business Intelligence Engineer II, AGI

As a Business Intelligence Engineer, you get a lot done. You work very efficiently and routinely deliver the right things. You have a department-wide view of the analytical solutions that you build, and you consistently think in terms of automating or expanding the results company-wide. You have performed multiple complex, and business critical analyses that serve major parts of the business. Your work and your approach to work are exemplary - you drive best practices and set standards for your team. Other analytical individuals in your department regard you as an expert in one or more analytical areas. You show strong analysis making technical trade-offs between your group s short term and long term business needs, and the needs of the company as a whole. When confronted with discordant views, you find the best way forward and convince your team. You are vocally self-critical. You proactively contribute to knowledge-sharing across the Amazon analytical community. You demonstrate resilience and navigate difficult situations with composure and tact.

Amazon has a culture of data-driven decision-making, and demands business intelligence that is timely, accurate, and actionable. Our environment is very fast-paced, and requires someone who is flexible, detail-oriented, passionate about the customer and comfortable working with numerous stakeholders across the organization and worldwide.


We are looking for a Business Intelligence Engineer to help us extract meaning from large volumes of data to make the right business decisions. The candidate will have to set the right vision, strategy and roadmap and work alongside with stakeholders in the organization to make it happen. The candidate knows and loves working with business intelligence tools, can model multidimensional datasets, and can partner effectively with business leaders to answer key business questions. You are analytical and creative, and you don t quit.


Primary Responsibilities
Engage with leadership and diversified customer groups to understand the needs and recommend business intelligence solutions.
Partner with Data engineering team to define the data elements and data structure that the team should leverage to enable analytical capabilities.
Design, implement, and support platforms that provide business teams ad-hoc access to large datasets (eg data visualization tools for non-tech business users)
Interface with business customers, gathering requirements and delivering 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 the operational and quality metrics.
Be connected and influential within the Amazon analyst community. Work with Data engineering, Software development teams to enable the appropriate capture and storage of key data points.


Key job responsibilities
Passionate about working with huge data sets and be someone who loves to bring datasets together to answer business questions. You should have deep expertise in creation and management of datasets Exposure at implementing and operating stable, scalable data flow solutions from production systems into end-user facing applications/reports. These solutions will be fault tolerant, self-healing and adaptive.
Detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion.
Excellent business and communication skills to be able to work with business owners to develop and define key business questions and to build data sets that answer those questions - 4+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 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
- Bachelors degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field