DESCRIPTION Are you excited about uncovering actionable insight to improve delivery experience? Do you get excited about operating in an ambiguous and fast moving environment? Are you looking for an opportunity to work with cross functional teams, and build decision-driven analytics solution for work that is critical to Amazon's continued ability to deliver smiles in communities? The DSP Analytics Team has an exciting opportunity for a Business Intelligence Engineer (BIE) to make an impact on the Amazon's Delivery Service Partner (DSP) program.
The goal of Amazon's DSP organization is to exceed the expectations of our customers by ensuring that their orders, no matter how large or small, are delivered as quickly, accurately, and cost effectively as possible. To meet this goal, Amazon is continually striving to innovate and provide best-in-class delivery experience through the introduction of pioneering new products and services in the last mile delivery space. Come join us and help us make history!
We are looking for an innovative and highly-motivated BIE who can think holistically through multidimensional problems to understand how systems work together to identify and execute both tactical and strategic projects which drive improvements to DSP programs. You will work closely with engineering & science teams, product managers, program managers, business coaches, capacity planners and org leaders to deliver end-to-end data solutions aimed at continuously enhancing overall capacity planning of DSP programs. In this role, you will dive deep into disparate datasets to improve our understanding of various components involved in Last Mile delivery, build decision-driven analytics to enable DSP growth and increase DSP capacity flexibility and reliability, improve tooling to scale up capacity planning processes across programs, and extract actionable insight to level up plan accuracy and process efficiency.
Key job responsibilities
- Earn the trust of your customers and stakeholders by continuing to constantly obsess over their business use cases and data needs, and helping them solve their problems by scaling data and tech solutions.
- Manage and execute analytics solutions end-to-end including project management, data gathering and modeling, problem solving, and communication of insights and recommendations.
- Build high quality data architecture and ETL data pipelines using SQL, Scripting and other ETL tools.
- Retrieve and analyze data using a broad set of Amazon's data technologies (ex. Redshift, AWS S3, Amazon Internal Platforms/Solutions) and resources, knowing how, when, and which to use.
- Design, build, and maintain automated reporting, dashboards, and ongoing analysis to enable data driven decisions across our team and with partner teams.
- Report key insight trends using statistical rigor to simplify and inform the larger team of noteworthy trends that impact the business.
- Partner with scientists to scale and expand science models through model and architecture improvements
- Be connected and influential within the Amazon BI and Data Engineering (DE) community. Work with DE and software development teams to enable the appropriate capture and storage of key data points.
About the team
We are the centralized Amazon DSP Analytics team with the vision to build best-in-class analytics solutions to support our internal and external DSP stakeholders and partners for making data driven decisions org-wide. We believe in promoting and using ideas to disrupt the status quo. In our team, you will have the opportunity to dive deep into complex business and data problems, drive high-impact and large scale data solutions and raise the bar for engineering and operational excellence. We have exceptionally talented and fun loving team members, and we love to share ideas and learnings with each other.
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA BASIC QUALIFICATIONS - Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience writing complex SQL queries
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with forecasting and statistical analysis
