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Job Type

Full Time

Job Description

Job Title: Cloud Architect / Principal Cloud Architect

Experience: 15+ Years

Work Mode: Noida (On-Site)

Employment Type: Full-Time


Role Overview

Cloud Architect

technical authority


Key Responsibilities

Cloud Architecture & Governance

  • Architect

    large-scale, secure, reliable, and compliant cloud solutions

    across AWS and multi-cloud environments.
  • Design and govern

    multi-cloud landing zones

    , workload placement strategies, interoperability, and account/subscription structures.
  • Lead

    cloud modernization initiatives

    leveraging microservices, containers, and cloud-native design patterns.
  • Define enterprise architecture standards across

    compute, networking, storage, IAM, automation, and data services

    .
  • Drive

    architecture governance

    through HLD/LLD reviews, ADRs, and design forums.

High Availability, Disaster Recovery & Backup

  • Define and own

    HA/DR strategies

    , including regional and multi-region failover models.
  • Establish

    RPO/RTO objectives

    , cross-region replication, and automated recovery workflows.
  • Design and manage

    snapshot lifecycle policies

    , backup, and restore strategies across

    cloud and hybrid environments

    .
  • Implement and govern backup technologies including

    Velero, cloud-native backup services, and hybrid backup solutions

    .

Kubernetes & Platform Engineering

  • Architect

    multi-region Kubernetes platforms

    (EKS/AKS/GKE) with strong governance and security controls.
  • Design and implement

    service mesh architectures

    (Istio, Consul) and

    zero-trust networking

    models.
  • Define platform-level

    observability standards

    covering logs, metrics, traces, SLIs, and SLOs.
  • Partner with

    DevOps and SRE teams

    to drive CI/CD, GitOps, platform automation, and reliability engineering practices.

Integration, Messaging & Streaming

  • Architect event-driven and integration solutions using

    Kafka, message queues, and streaming platforms

    .
  • Define scalable, fault-tolerant messaging architectures supporting real-time and asynchronous workloads.

FinOps, Leadership & Enablement

  • Support

    cloud cost governance

    , optimization strategies, and

    chargeback/showback models

    .
  • Lead

    architecture reviews, proof-of-concepts (PoCs)

    , and creation of

    reference architectures and blueprints

    .
  • Mentor architects and senior engineers, fostering best practices in cloud-native design and platform engineering.
  • Collaborate closely with

    security teams

    to implement IAM guardrails, CSPM/CWPP controls, and compliance automation.


Must-Have Skills & Experience

  • 15+ years

    of experience in

    enterprise IT and cloud architecture

    .
  • Deep expertise in

    AWS

    , including compute, networking, IAM, storage, and serverless services.
  • Strong experience designing

    multi-cloud architectures and landing zones

    .
  • Advanced

    Kubernetes architecture

    expertise (multi-region, service mesh, governance, and security).
  • Proven experience with

    HA/DR design

    , cross-region replication, and snapshot orchestration.
  • Hands-on knowledge of

    backup and recovery technologies

    (Velero, cloud-native, hybrid solutions).
  • Strong experience in

    hybrid-cloud networking

    : Direct Connect, ExpressRoute, VPN, TGW, SD-WAN.
  • Expertise in

    cloud security architecture

    , including CSPM/CWPP tools and zero-trust models.
  • Strong understanding of

    SRE concepts

    : SLIs/SLOs, automation, resilience testing, chaos engineering.
  • Experience architecting

    Kafka and streaming integrations

    .
  • Proven implementation of

    observability pipelines

    (logs, metrics, traces).
  • Strong

    Infrastructure as Code (IaC)

    skills using

    Terraform and CloudFormation

    .
  • Excellent documentation skills:

    HLD, LLD, ADRs

    , and architecture governance leadership.


Good-to-Have

  • Experience with

    AI/ML platforms

    or

    large-scale data ecosystems

    .
  • Exposure to advanced analytics, data lakes, and streaming data platforms.

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