Business Intel Engineer
5 days ago
The Benchmarking program within Design team is focused on measuring and continuously improving the performance of Amazon’s Last Mile delivery station designs and operational layouts across safety, cost, associate experience, and efficiency metrics. You will work closely with stakeholders to translate business requirements into scalable, automated BI solutions that enable data-driven decision making.
As an Amazon Business Intelligence Engineer you will be working in one of the world's largest and most complex data warehouse environments. You should have deep expertise in the design, creation, management, and business use of extremely large datasets. You should have excellent business and communication skills to be able to work with business owners to develop and define key business questions, and to build data sets that answer those questions. You should be expert at designing, implementing, and operating stable, scalable, low-cost solutions to flow data from production systems into the data warehouse and into end-user facing applications. You should be able to work with business customers in understanding the business requirements and implementing reporting solutions. The potential candidate will explore and utilize generative BI and machine learning solutions to innovate and find most efficient solution for complex business problems.
Above all you should be passionate about bringing large datasets together to answer business questions and drive change.
Key job responsibilities
- Partner with internal stakeholders across multiple teams, gathering requirements and delivering end to end business intelligence solutions.
- Partner with data engineers to identify the source of data and create a data pipeline to collect necessary business inputs to deliver the analytical product.
- Support benchmarking and innovation program pilot studies by building robust pilot analyses plan, data collection processes, and analyzing the output to deliver final recommendations.
- Utilize predictive analytics, machine learning and generative BI tools to continuously improve the quality of the analytics products and effectiveness of the business insights.
- Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.
- Design, develop, and implement BI dashboards, reports, and analytical tools to support the WW Design Benchmarking program and the broader WW Last Mile Design Engineering team.
- Maintain and enhance existing BI products used by the WW Design Engineering team.
- Collaborate with cross-functional partners and stakeholders to gather business requirements, identify data sources, and deliver actionable insights.
- Apply advanced analytics techniques, including predictive modeling and machine learning, to uncover meaningful trends and recommend impactful improvements.
- Ensure BI solutions are scalable, maintainable, and follow best practices in data management and visualization.
- Continuously optimize data pipelines, reporting processes, and analytical workflows to improve operational efficiency.
- Mentor and share knowledge with the broader team of benchmarking and design engineers.
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA | Nashville, TN, 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 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
PREFERRED QUALIFICATIONS
- 5+ years of experience in a business intelligence or data analytics role- Expert-level knowledge of AWS data services (e.g., EC2, DynamoDB, S3, Redshift)
- Experience with predictive analytics, machine learning, and generative BI tools
- Familiarity with design, engineering, and operational data in a logistics environment
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