Business Intelligence Engineer II, Rapid and Rural Logistics, R2L
Job Description
The Rapid & Rural Logistics (R2L) team is seeking a Business Intelligence (BI) Engineer to join the org. The R2L team that includes rush service and super rural delivery covers a portfolio of high-growth businesses with unique fulfillment and operational capabilities such as Sub Same Day (SSD), Rural Super Rural + (RSR+), and SSD Direct. R2L exists solely to meet the goal of quick, accurate delivery and this is constantly being challenged and changed, adapting to our customer demands and improved. To meet this goal, R2L must remain flexible at all times, adapting with all of the changes and growth that comes our way. As a Business Intelligence (BI) Engineer, your focus will be on process automation, operational insight, and other analytical support to stakeholders. The team partners closely with delivery and operations teams.The ideal candidate will draw upon advanced analytical, problem solving skills, and a passion for building solution towards automated operational management. The successful leader of this team will collaborate effectively with internal end-users, cross-functional stakeholders and technical teams to drive for automation of our operational processes for future innovation. They must be a self-starter, comfortable with ambiguity, and able to think big and be creative to support a rapidly growing business. Key job responsibilitiesThe successful candidate is a seasoned data professional with a strong bias for action, Proficiency with data visualization tools like QuickSight and Tableau, data modeling, ETL (Extract, Transform, Load), SQL, and scripting skills.Own the design, and development of projects to drive key business decisions. A typical day in this role provides an opportunity to build innovative data solutions with large-scale systems, identify high-priority work and projects that maximize results for key stakeholders, and solve complex problems that impact company-wide strategic decisions. Further, you will help automate processes by developing deep-dive tools, and dashboards to communicate these insights to the business teams. Successful members of this team collaborate effectively with business customers and cross-functional data management teams to solve problems and implement new solutions.A day in the life• Take detailed requirements from stakeholders to deeply understand their current manual processes and pain points• Think creatively to identify opportunities to solve problems using technology-driven solutions• Design and implement the optimal automation solutions to address stakeholder needs• Respond to ad-hoc requests and provide support as needed• Thoroughly document all processes, solutions, and learnings to ensure knowledge capture and sharing• Documentation
Locations
- United States, TN, Nashville, Nashville, TN, United States
- United States, WA, Bellevue, Bellevue, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
135,000 - 185,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experienceintermediate
- - Experience with data visualization using Tableau, Quicksight, or similar toolsintermediate
- - Experience with data modeling, warehousing and building ETL pipelinesintermediate
- - Experience in Statistical Analysis packages such as R, SAS and Matlabintermediate
- - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modelingintermediate
Required Qualifications
- - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience (experience, 3 years)
- - Experience with data visualization using Tableau, Quicksight, or similar tools (experience)
- - Experience with data modeling, warehousing and building ETL pipelines (experience)
- - Experience in Statistical Analysis packages such as R, SAS and Matlab (experience)
- - Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling (experience)
Preferred Qualifications
- - Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift (experience)
- - Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $89,600/year in our lowest geographic market up to $185,000/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. (experience)
Responsibilities
- The successful candidate is a seasoned data professional with a strong bias for action, Proficiency with data visualization tools like QuickSight and Tableau, data modeling, ETL (Extract, Transform, Load), SQL, and scripting skills.
- Own the design, and development of projects to drive key business decisions. A typical day in this role provides an opportunity to build innovative data solutions with large-scale systems, identify high-priority work and projects that maximize results for key stakeholders, and solve complex problems that impact company-wide strategic decisions. Further, you will help automate processes by developing deep-dive tools, and dashboards to communicate these insights to the business teams. Successful members of this team collaborate effectively with business customers and cross-functional data management teams to solve problems and implement new solutions.
