Business Intel Engineer - II, Robotics, Robotics, Global Operations - Artificial

Overview

Amazon Robotics is at the forefront of applying state‑of‑the‑art artificial intelligence to solve real‑world challenges at unprecedented scale. Our fulfillment centers handle more individual items than any company in the world, combining computer vision, mobile robots, advanced end‑of‑arm tooling, and high‑degree‑of‑freedom movement with state‑of‑the‑art AI. We collaborate with customers across Amazon worldwide to conceive, develop, prototype, and deploy intelligent robotic systems that push the boundaries of industrial automation.

Within Amazon Robotics, the Global Operations – Artificial Intelligence (GO‑AI) team enables Amazon to accelerate and scale the next generation of AI‑powered robotic solutions. We are transforming how complex visual reasoning tasks are performed across Amazon’s robotics operations, moving from traditional manual data annotation processes to state‑of‑the‑art foundation model solutions.

As a Business Intelligence Engineer on GO‑AI’s Technology & Development Team, you’ll work with cross‑functional teams (Science, Software, Data, BIE) managing massive‑scale, proprietary datasets to develop foundation models that achieve human‑level performance on complex real‑world tasks. Your work will directly impact millions of daily operations across Amazon’s global fulfillment network.

• Design, develop, and operate scalable, performant data warehouses (Redshift) tables, data pipelines, reports and dashboards.
• Develop moderately to highly complex data processing jobs using appropriate technologies (SQL, Python, Spark, AWS Lambda, etc.).
• Create dashboards and reports.
• Collaborate with stakeholders to understand business domains, requirements, and expectations, and work with owners of data source systems to gain insights into capabilities and limitations.
• Deliver minimally to moderately complex data analysis.
• Adopt best practices in reporting: data integrity, test design, validation, and documentation.
• Ensure excellence in verbal and written communication.
• Comfortable wearing multiple hats and go above and beyond to drive results.

We offer a full range of benefits for you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full‑time employees include medical, dental, vision coverage, maternity and parental leave, paid time off, and a 401(k) plan.

The Amazon Robotics (AR) Technology Enablement Services (TES) team enables AR’s people, purpose, and place to deliver the future. We remove barriers, drive organizational productivity, and foster growth. We serve AR leadership, product customers, and employees, collaborate with teams throughout FTR, and design and iterate on learning, development, and engagement solutions to support operators and employees. We synthesize and articulate AR’s long‑term strategy, near‑term goals, product roadmaps, and workforce strategy, and develop and manage cross‑organizational mechanisms, reporting, programs, and sustainability efforts.

• 3+ years of analyzing and interpreting data with Redshift, Oracle, No
  
  SQL, etc.
• Experience with data visualization using Tableau, Quicksight, or similar tools.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience with 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 translating customer needs into business requirements.
• Experience writing and optimizing SQL queries with large‑scale, complex datasets.
• Experience documenting data models, pipelines, and metrics definitions.

• Experience with AWS services such as EC2, Dynamo
  
  DB, S3, and Redshift.
• Experience in data mining, ETL, and working with databases in a business environment with large‑scale, complex datasets.
• Experience using Python scripting to process data for modeling.
• Experience…