Amazon's Transportation team is looking for an innovative, analytical, and customer-obsessed Business Intelligence Engineer to join our Analytics team. The ideal candidate will bring strong attention to detail, excellent communication skills, and the ability to manage multiple analytical projects efficiently. We value professionals who can translate complex data into actionable insights and communicate these effectively to stakeholders at all levels.
In this role, you will be responsible for developing and implementing solutions that help detect and prevent operational issues before they impact our customers. Your analytical mindset and sound judgment will be essential in prioritizing projects and driving improvements to enhance the customer experience. We're looking for someone who can think strategically while maintaining a strong focus on execution.
The successful candidate will define problems and build analytical frameworks to streamline operations, leveraging data analysis to identify process gaps and opportunities for improvement. You'll collaborate closely with cross-functional teams to implement solutions and drive meaningful change. Key responsibilities include conducting in-depth data analysis, creating and maintaining dashboards, and regularly sharing insights with internal stakeholders to support data-driven decision-making.
Success in this position requires adaptability, quick learning, and a passion for using data to solve complex business problems. You'll have the opportunity to work with large-scale datasets and advanced technologies while contributing to the continuous improvement of our transportation network.
Key job responsibilities
- Apply multi-domain expertise to daily activities and own the end-to-end project roadmap.
- Translate complex or ambiguous business problems into clear analysis requirements, maintaining high standards throughout execution.
- Define and review analytical approaches with stakeholders, ensuring alignment with business objectives.
- Proactively work with stakeholders to develop use cases and standardized outputs, communicating effectively across teams.
- Develop efficient queries using advanced SQL techniques (e.g., window functions, virtual tables) to work with various data sources, minimizing post-processing needs.
- Scale data processes and reports, creating updateable queries for clients and collaborating with data engineering for full-scale automation.
- Maintain comprehensive knowledge of available data across the business to support complex and comparative analyses.
- Ensure data fidelity by cross-referencing multiple sources when necessary.
- Actively manage project timelines and deliverables, focusing on team interactions and communication.
- Provide regular updates to stakeholders, including progress reports and identification of potential roadblocks with proposed solutions.
- Lead medium-sized analytical projects within the organization, representing the team effectively.
- Stay current with emerging technologies and best practices in business intelligence and data analytics.
A day in the life
- Solve ambiguous analyses with less well-defined inputs and outputs; drive to the heart of the problem and identify root causes
- Have the capability to handle large data sets in analysis through the use of additional tools
- Derive recommendations from analysis that significantly impact a department, create new processes, or change existing processes
- Understand the basics of test and control comparison; may provide insights through basic statistical measures such as hypothesis testing
- Identify and implement optimal communication mechanisms based on the data set and the stakeholders involved
- Communicate complex analytical insights and business implications effectively
About the team
AOP (Analytics Operations and Programs) team is missioned to standardize BI and analytics capabilities, and reduce repeat analytics/reporting/BI workload for operations across IN, AU, BR, MX, SG, AE, EG, SA marketplace.
AOP is responsible to provide visibility on operations performance and implement programs to improve network efficiency and defect reduction. The team has a diverse mix of strong engineers, Analysts and Scientists who champion customer obsession.
We enable operations to make data-driven decisions through developing near real-time dashboards, self-serve dive-deep capabilities and building advanced analytics capabilities.
We identify and implement data-driven metric improvement programs in collaboration (co-owning) with Operations teams.- 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 with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- 4+ years of ecommerce, transportation, finance or related analytical field experience- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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