Business Intelligence Engineer II, SFS
Amazon
Full-time
On-site
Bellevue, Washington, United States
$89,600 - $185,000 USD yearly
Amazon’s Marketplace services over 2 million Sellers disrupting traditional notions of retail marketplace and connecting millions of businesses, big and small, to millions of Customers within the Amazon.com marketplace. The Marketplace business exceeds 50% of the total Amazon.com sales and each year, tens of thousands of businesses join the marketplace adding millions of new products.
The Seller Fulfillment Services (SFS) team is seeking a experienced Business Intelligence Engineer to own strong and complex analytics and to bring in comprehensive deep dives to help drive the growth of SFS Business.
The candidate should have expertise in designing and implementing scalable data warehouse infrastructure and build dynamic visualization platform and self serve tools for end-user consumption. Candidate should have solid knowledge in data engineering to develop efficiency DW pipelines given the scale of the dataset SFS is working with. Moreover, the candidate should have ability in using advanced techniques, for example scripting language and building statistical models, to drive complex insights analysis.
Our ideal candidate thrives in a fast-paced environment, enjoys the challenge of highly complex business scenarios and is passionate about data and analytics. To be successful in this role you will need to have excellent analytical, data warehousing and communication skills.
Key job responsibilities
- Design, implement, and deploy BI solutions. You successfully solve difficult and/or loosely structured problems. You are able to refine requirements from business stakeholders into a functional design that solves the problem
- Have a solid understanding of data design approaches and analysis techniques (and how to best use them)
- Able to work independently and with your team to deliver BI solutions successfully
- Demonstrate high quality (e.g., maintainable, efficient, well-documented) work consistently and incorporates best practices. Your team trusts your work
- You focus on operational excellence: constructively identifying quality issues, proposing solutions when necessary, taking on projects that improve your team’s BI solutions, and making them better and easier to maintain
- You create source-of-truth datasets using SQL; you leverage scripting language i.e. Python to create automation and reduce manual processes
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 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 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 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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.
The Seller Fulfillment Services (SFS) team is seeking a experienced Business Intelligence Engineer to own strong and complex analytics and to bring in comprehensive deep dives to help drive the growth of SFS Business.
The candidate should have expertise in designing and implementing scalable data warehouse infrastructure and build dynamic visualization platform and self serve tools for end-user consumption. Candidate should have solid knowledge in data engineering to develop efficiency DW pipelines given the scale of the dataset SFS is working with. Moreover, the candidate should have ability in using advanced techniques, for example scripting language and building statistical models, to drive complex insights analysis.
Our ideal candidate thrives in a fast-paced environment, enjoys the challenge of highly complex business scenarios and is passionate about data and analytics. To be successful in this role you will need to have excellent analytical, data warehousing and communication skills.
Key job responsibilities
- Design, implement, and deploy BI solutions. You successfully solve difficult and/or loosely structured problems. You are able to refine requirements from business stakeholders into a functional design that solves the problem
- Have a solid understanding of data design approaches and analysis techniques (and how to best use them)
- Able to work independently and with your team to deliver BI solutions successfully
- Demonstrate high quality (e.g., maintainable, efficient, well-documented) work consistently and incorporates best practices. Your team trusts your work
- You focus on operational excellence: constructively identifying quality issues, proposing solutions when necessary, taking on projects that improve your team’s BI solutions, and making them better and easier to maintain
- You create source-of-truth datasets using SQL; you leverage scripting language i.e. Python to create automation and reduce manual processes
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 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 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 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. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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.