Business Intelligence Engineer II, DSP Analytics

AmazonBellevue, WashingtonOn-siteFull-timeMid level, 2–5 yearsListed 28 minutes ago

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About this role

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
- Accelerate GenAI Footprint: Partner with Data Engineers to expand our GenAI tools and improve developer productivity, while raising the bar on data quality and enabling intelligent automation across capacity planning workflows.
- 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 WW DSP Analytics team with the vision to enable data, insights and science driven decision-making. We have exceptionally talented and fun loving team members. In our team, you will have the opportunity to dive deep into complex business and data problems, drive large scale technical solutions and raise the bar for operational excellence. We love to share ideas and learnings with each other. We believe in promoting and using ideas to disrupt the status quo.

Basic Qualifications

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience writing complex SQL queries
- 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

Preferred Qualifications

- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, 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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits .

USA, WA, Bellevue - 99,500.00 - 160,000.00 USD annually