# Business Intelligence Engineer, AOP - ROW APEX at Amazon

Amazon is hiring a Business Intelligence Engineer, AOP - ROW APEX in Hyderabad, India. Level rates it Works on AI ●●●○; you can [apply on Amazon](https://jobsbylevel.com/go/4b763aff-a37e-4521-81bd-c5b1a2ba9e54?utm_medium=ai-agent).

AI Level 3, AI centrality 66 out of 100. IN, TS, Hyderabad.

## Details

- Company: [Amazon](https://jobsbylevel.com/companies/amazon)
- AI level: AI Level 3 (score 66 out of 100)
- Location: IN, TS, Hyderabad
- Posted: July 2, 2026
- Apply: https://jobsbylevel.com/go/4b763aff-a37e-4521-81bd-c5b1a2ba9e54?utm_medium=ai-agent
- Free CV review for this job: https://jobsbylevel.com/cv-review?job=business-intelligence-engineer-aop-row-apex-at-amazon-dac385

## Prepare for this job

The job page lists 3 likely interview questions for this offer, with a CV checklist: https://jobsbylevel.com/jobs/business-intelligence-engineer-aop-row-apex-at-amazon-dac385

## Description

The Analytics Ops and Programs (AOP) team in Hyderabad is looking for an innovative, hands-on, and customer-obsessed Business Intelligence Engineer who wants to work at the intersection of analytics and science. This role sits at a rare vantage point with high growth prospects: on one side are ML/OR models making split-second, cost-saving decisions across the Ops network; on the other is the analytical depth required to understand why those models succeed, where they fall short, and what needs to change. You won't just observe these models from the outside — you'll own them alongside the Scientists. Their performance, their enhancements, and their evolution over time will be your responsibility. When a model needs a new feature, a re-calibrated threshold, or a fundamentally different approach for a particular corridor or condition, you'll be the one driving that forward in partnership with the scientists who built it — and in some cases you'll own those models directly. The technical challenges here are genuinely complex and rewarding. You'll work with large-scale data flowing through automated, near real-time pipelines. You'll design reporting and monitoring frameworks that are as robust as the systems they watch. You'll apply statistical rigor to evaluate model performance in production, design experiments to validate enhancements, and quantify impact in an environment where conditions shift daily. Beyond monitoring, you'll identify what's broken, propose what to build next, and own the analytical path from hypothesis to deployed improvement. This is a role without a single well-worn toolkit — you'll continuously sharpen your skills across data engineering, statistical analysis, and model evaluation to keep pace with the problems in front of you. What makes this role compelling is the combination of ownership and impact. The products you work on drive millions in cost savings for Amazon Ops, and you'll be involved in applied, cutting-edge work. You'll need to be comfortable with ambiguity: many of the most important questions here haven't been cleanly articulated yet — they emerge from patterns in the data, from model behavior that doesn't match expectations, and from edge cases that only surface under certain network conditions. Strong statistical foundations, fluency in SQL, Python, and AWS services, and experience building scalable BI solutions are essential. Your ability to move between deep technical analysis and clear stakeholder communication — and to own outcomes end-to-end rather than just deliver reports — is what will make you exceptional. The ideal candidate is detail-oriented with superior verbal and written communication, strong organizational skills, and excellent technical skills, and is able to juggle multiple tasks at once. You must be able to identify problems before they happen, prioritize accurately, make sound judgments, and get the right things done. This job requires you to constantly hit the ground running and learn quickly. Key job responsibilities Partner with Scientists to own ML/OR models in production — monitoring performance, driving enhancements, and in some cases owning models end-to-end. Apply statistical rigor to evaluate models, design experiments, and quantify business impact. Build scalable, automated data pipelines that inform decision-making and feed model development. Own the design and maintenance of BI solutions, metrics, and reporting/monitoring frameworks. Perform root-cause analysis and ensure data accuracy for new and existing tools and models. Manage projects end-to-end — from data gathering and modeling through to communicating insights and recommendations. Collaborate with Scientists, Data Engineers, SDEs, Product, and Program teams to align deliverables with requirements. A day in the life 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,

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/business-intelligence-engineer-aop-row-apex-at-amazon-dac385

Source: https://jobsbylevel.com/jobs/business-intelligence-engineer-aop-row-apex-at-amazon-dac385

## Cite this page

Level. https://jobsbylevel.com/jobs/business-intelligence-engineer-aop-row-apex-at-amazon-dac385.

Get job alerts: https://jobsbylevel.com/newsletter