AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we’re the people who keep the cloud running. We support all AWS data centers and all of the servers, storage, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we’re looking for talented people who want to help.
You’ll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You’ll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you’ll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.
Are you interested in building highly impactful business intelligence (BI) solutions in a mixed team of BIEs, Data Scientists, Data Engineers, and SDEs? If so, you should consider a role in AWS Hardware Engineering Services.
We are responsible for designing, qualifying, and maintaining server solutions for AWS and its customers. The Data Science and Analytics team supports the broader Hardware Engineering organization by acting as conduits between the data and the business. As a Business Intelligence Engineer in our team, you will support the design, implementation, and delivery of BI solutions in a complex problem space that has a long-term impact on a business, organization, and technology. You will gain exposure to both Data Science and Data Engineering disciplines, while developing your technical skills and leadership ability.
The ideal candidate will be experienced in the areas of data and business intelligence systems. You have a demonstrated record of driving new analytical solutions from inception to launch. You are highly skilled with SQL, have experience developing ETL processes, understand data visualization tools such as QuickSight, and have familiarity with at least one scripting language.
About the team
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Amazon Web Services (AWS) values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
- 5+ years of experience in analyzing, interpreting and reporting data
- 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
- Experience working directly with business stakeholders to translate between data and business needs
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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 for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $117,300/year in our lowest geographic market up to $202,800/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
Business Intelligence Engineer, Data Science & Analytics
Posted: | 19 Dec 2024 |
---|---|
Company: | Amazon |
Category: | Business Intel Engineer |
Country: | US - United States |
State: | None - None |
City: | Seattle |
Zip code: | None |