Business Intelligence Engineer, Worldwide Customer Service Finance

AI in this role

Build and maintain BI solutions, data pipelines, and automated reporting tools to support finance and customer service operations.

redshiftoraclenosqlsqletltableauquicksightpythonrsasmatlabaws+3

data-analysisdata-modelingdata-warehousingstatistical-analysisautomated-reporting

As a Business Intelligence Engineer with Worldwide Customer Services Finance team, you will help identify opportunities and implement solutions to improve Finance facing systems and tools. You will be responsible for functional and technical design of BI solutions for the team, including user interfaces, data architecture and data processing. Further, you will drive automation of processes through self-service deep-dive tools, and dashboards to deliver insights to the business teams. While onboarding new functionalities you’ll ensure the solution implemented will fulfill business needs in an efficient scalable way.

Everything we do at Amazon is focused on being “Earth’s Most Customer-Centric Company”. At the core of this customer centricity is the Amazon Customer Service organization. We are currently looking for a highly analytical, creative and forward-thinking Business Intelligence Engineer to join our Customer Service Finance team.

Key job responsibilities
You will partner with Engineering, Operations Finance and Capacity Planning teams around the world to standardize our processes, improve front-end reporting, and create mechanisms to scale tools to accommodate rapidly changing business needs. You will be responsible for building and maintaining efficient near real-time data pipelines that bring together important operations and finance data from disparate data sources.

Basic qualifications

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 2+ years of SQL, ETL or Oracle experience
- 1+ years of processing large, multi-dimensional datasets from multiple sources experience
- 1+ years of performing statistical analysis experience
- 1+ years of developing automated reporting experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- 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
- Experience in Statistical Analysis packages such as R, SAS and Matlab

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.

How we rate this

Business Intelligence Engineer, Worldwide Customer Service Finance at Amazon rates 20 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Data AnalysisData ModelingData WarehousingStatistical AnalysisAutomated ReportingRedshiftOracleNosql

Questions you could be asked

Tell me about a project where data analysis was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?
Tell me about a project where data warehousing was part of your work. What did you do?
Tell me about a project where statistical analysis was part of your work. What did you do?
Tell me about a project where automated reporting was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Data Analysis, Data Modeling, Data Warehousing, Statistical Analysis, and Automated Reporting. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.

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