Manager

Req# 30047709 Lead DevOps Engineer (Manager Role) Open for Bangalore and Gurgaon Responsibilities As a Lead DevOps Engineer, you will design, build and operate the cloud platform and infrastructure automation that underpins Clara Technology & Solutions. You will treat infrastructure as a product, enabling engineering teams to deliver securely and at scale. Key responsibilities include: Design, build and maintain production-grade Infrastructure as Code using Terraform and related tooling , creating reusable, opinionated and well-tested reusable assets with versioning, release strategies, and policy-as-code, security and compliance controls built in. Architect and operate solutions across the Azure platform, leveraging services such as Databricks , Azure Functions, Application Gateway, API Management, Storage Accounts and Service Bus to deliver reliable, scalable infrastructure. Build and maintain advanced CI/CD pipelines in Azure DevOps and GitHub, using reusable templates, strong code-review and branching workflows, and integrated automated testing and policy enforcement. Implement and uphold Azure security and identity best practice, including RBAC, Entra ID, enterprise applications, managed and workload identities, and zero-trust architectures. Develop automation, validation tooling and pre-commit hooks in Bash, PowerShell to improve infrastructure quality, consistency and the developer experience. Deliver internal platforms as products, providing clear abstractions, reusable artefacts and self-service capabilities, supported by high-quality, maintainable documentation. Collaborate with engineering teams and stakeholders, clearly articulating complex technical concepts and championing engineering best practice across the function Experience & Knowledge Requirement - Required Production‑Grade Terraform Engineering: Enterprise‑ready IaC covering robust module design and composition, reusable and opinionated abstractions, versioning and release strategies, automated testing (validation, unit tests, policy‑as‑code), security and compliance controls, and CI/CD‑driven delivery for reliable, scalable infrastructure. Azure Ecosystem Knowledge: Strong all‑round understanding of the Azure platform, with hands‑on experience across cloud application services such as Databricks, Azure Functions, Application Gateway, API Management, Storage Accounts, Service Bus etc. Azure Security & Identity: Solid understanding of RBAC, Entra ID, enterprise applications, managed and workload identities, and zero‑trust security architectures. Azure DevOps & GitHub: Advanced CI/CD pipelines with reusable templates, strong code‑review and branching workflows, and integrated automated testing and policy enforcement. Scripting & Automation: Proficient in languages such as Bash, PowerShell, or Python for validation tooling, pre‑commit hooks, automation, and infrastructure testing. Communication & Product Mindset: Ability to clearly articulate complex technical concepts, treat infrastructure as a product with real users, and produce high‑quality, maintainable documentation. Azure Networking: Solid understanding of Virtual networks and subnet design, private endpoints, private DNS zones, NSGs, Application Gateway, and network segmentation patterns. Platform Thinking: Experience building internal platforms as products, with reusable artifacts, clear abstractions, and self‑service capabilities for engineering teams. Advanced Infrastructure Testing: Familiarity with integration testing for IaC, contract testing between platform and consumers, chaos engineering concepts, and automated drift detection. Platform Technologies: Exposure to tools such as Backstage, custom CLI development, and API‑driven infrastructure provisioning and enablement. Databricks & Data Platforms: Experience with Azure Databricks workspace configuration, Unity Catalog administration, and common AI/ML infrastructure patterns. Desirable Azure Networking: Solid understanding of Virtual networks and subnet design, private endpoints, private DNS zones, NSGs, Application Gateway, and network segmentation patterns. Platform Thinking: Experience building internal platforms as products, with reusable artifacts, clear abstractions, and self‑service capabilities for engineering teams. Advanced Infrastructure Testing: Familiarity with integration testing for IaC, contract testing between platform and consumers, chaos engineering concepts, and automated drift detection. Platform Technologies: Exposure to tools such as Backstage, custom CLI development, and API‑driven infrastructure provisioning and enablement. Databricks & Data Platforms: Experience with Azure Databricks workspace configuration, Unity Catalog administration, and common AI/ML infrastructure patterns.