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REQUIREMENT_ID_1361 • 3-DAY_ACTIVE_POLICY

Data Centre Engineering Operations Engineer, Data Centre Engineering Operations

Company
Company Amazon
Type
Opportunity Type Internship
Salary
Stipend / Salary ₹15 LPA - ₹20 LPA
Location
Location Mumbai, Maharashtra, India
Posted Date
Posted Date Sep 26, 2026
Data centre operations Electrical power systems Mechanical HVAC systems Fire suppression Asset management Incident management Root cause analysis SOP development Technical documentation Vendor management Python scripting SCADA/BMS Preventive maintenance KPI reporting
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Amazon Placement Papers – Questions & Answers Open Resource ↗
Curated set of previous Amazon interview questions that help candidates understand the type of technical and aptitude problems asked.
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Amazon Recruitment Process Experiences Open Resource ↗
First‑hand accounts of candidates who have cleared Amazon's interview stages, useful for preparing strategy and expectations.
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Amazon Interview Preparation Guide Open Resource ↗
Comprehensive guide covering Amazon's interview format, common topics, and tips to ace each round.
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Algorithm Practice Problems Open Resource ↗
Large collection of coding problems to sharpen problem‑solving skills, essential for Amazon's technical assessments.

Bachelor's degree in Electrical Engineering, Mechanical Engineering, or a related discipline; Minimum 60% aggregate (or CGPA 6.0/10) in the qualifying degree; Graduation batch 2022‑2026; No active backlogs at the time of joining; Eligibility for 24x7 on‑call and shift work; Valid work authorization for India.

1
Round 1: Online assessment (aptitude & logical reasoning)
2
Round 2: Technical interview (facility engineering, problem‑solving, scenario based)
3
Round 3: Leadership Principles interview
4
Round 4: HR discussion (culture fit, compensation).
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform, serving millions of customers ranging from startups to Fortune 500 enterprises. AWS operates a massive global infrastructure that powers everything from e‑commerce sites to AI‑driven applications. In India, Amazon has built several state‑of‑the‑art data centres that host critical workloads for customers across the sub‑continent. These facilities are the backbone of the cloud, and keeping them running 24x7 requires a blend of cutting‑edge engineering, rigorous operational discipline, and a culture of relentless improvement. The Data Centre Engineering Operations team is at the heart of this effort, ensuring that every piece of equipment – from power distribution units to cooling towers – functions flawlessly and meets the highest safety and efficiency standards. The role of Data Centre Engineering Operations Engineer is a hands‑on, senior‑level position that acts as the single point of accountability for the mechanical, electrical, and fire‑suppression systems across Amazon’s Indian data‑centre portfolio. You will own the end‑to‑end lifecycle of infrastructure changes, incidents, and preventive maintenance, while collaborating with cross‑functional teams such as construction, security, logistics, and vendor management. The position demands a deep technical background, strong problem‑solving abilities, and the willingness to work in a 24x7 on‑call environment with rotating shifts. You will be instrumental in driving standardisation, automation, and continuous improvement across all facilities. Key responsibilities include: 1. Lead the planning, execution, and documentation of all data‑centre changes, events, incidents, and problem‑resolution activities. 2. Oversee preventive and corrective maintenance of electrical systems (sub‑stations, UPS, generators, PDUs, ATS, battery banks) and mechanical systems (CRAC/CRAH, chillers, cooling towers, pumps, valves). 3. Manage asset and inventory records, ensuring accurate tracking of critical equipment. 4. Develop and maintain method statements, SOPs, emergency response procedures, and technical documentation, driving consistency across sites. 5. Produce regular engineering performance reports, monitoring SLA and KPI compliance for facilities. 6. Provide hands‑on support for rack installations, de‑commissioning, equipment upgrades, and internal audits. 7. Conduct technical compliance audits and ensure timely closure of corrective action plans. 8. Coordinate with landlords, vendors, construction teams, and internal stakeholders to align on project timelines and safety standards. 9. Lead incident communication, trend analysis, and post‑mortem reporting to senior management. 10. Mentor junior engineers and contribute to the automation of routine operational tasks using scripting or infrastructure‑as‑code tools. The technical stack for this role includes a deep understanding of power distribution (transformers, switchgear, VFI UPS, DRUPS), backup power (diesel/gas generators, fuel systems), battery management, surge suppression, and harmonic filtering. On the mechanical side, expertise in HVAC systems (CRAC/CRAH, AHU), chilled water plants, cooling towers, and associated piping and control systems is essential. Familiarity with SCADA, BMS, and monitoring platforms, as well as basic scripting (Python, PowerShell) for automation, will be advantageous. Career growth at AWS is highly merit‑based. Successful engineers can progress to senior engineering roles, lead large‑scale facility programmes, or transition into technical program management, reliability engineering, or data‑centre design leadership. The exposure to cutting‑edge infrastructure, global best practices, and a culture that rewards innovation makes this an attractive opportunity for ambitious engineers. Why join Amazon? Apart from the brand prestige, Amazon offers a fast‑paced environment where you can work on some of the most complex infrastructure challenges in the world. Employees benefit from competitive compensation, comprehensive health benefits, continuous learning programs, and a culture that encourages ownership and long‑term impact. The inclusive work culture, focus on safety, and commitment to sustainability further enhance the employee experience.

Amazon — AI & Machine Learning Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC 📖
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource ↗
COMPANY GUIDE 🎯
Amazon Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Amazon and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource ↗
CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource ↗
Round 1: Online Assessment (OA)
Aptitude, Quantitative Logic & 2 Coding Problems
Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1
Core Tech Stack (Data centre operations, Electrical power systems, Mechanical HVAC systems, Fire suppression, Asset management, Incident management, Root cause analysis, SOP development, Technical documentation, Vendor management, Python scripting, SCADA/BMS, Preventive maintenance, KPI reporting) & Live Code Tracing
Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving
Database Schemas, APIs & Architecture Basics
Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion
Amazon Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
What is the bias-variance tradeoff and how do you prevent overfitting? Answer ▼
Model Answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer ▼
Model Answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer ▼
Model Answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer ▼
Model Answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Why do you want to join Amazon as a Data Centre Engineering Operations Engineer, Data Centre Engineering Operations?
Preparation Tip: Highlight Amazon's market reputation, recent tech innovations, and how your skills in Data centre operations directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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