Devops Engineer - Hybrid (Bengaluru)

Devops Terraform-5+ Years

The DevOps Engineer will be part of Engineering team working closely in collaboration with Data Platform Admins, Data Architects and Platform Architects.  

• Should have strong experience in Terraform concepts, hands-on in HCL language. 
• Hands-on experience in developing/configuring Terraform Modules. 
• Good exposure with best practices in building Terraform codes against Azure cloud (or any Cloud) 
• Exposure of managing Terraform state file in a complex infrastructure perspective. 
• Should have experience on source code and control management, branching, merging, labeling, and code consumption topology. (GIT) 
• Maintain a deep understanding of cloud data architecture, transition strategies and computing and technology systems. (Azure preferred) 
• Ideas of integrating Terraform with DEVOPS tools such as Azure DevOps. 
• Understanding and experience about Azure DevOps Pipelines and troubleshooting.  
• Skill of developing tasks in Azure DevOps with Terraform, Azure CLI, PowerShell and Python. 
• Build and maintain tools, solutions and microservices associated with deployment and our operations platform, ensuring that all meet our customer service standards and reduce errors 
• Leverage industry and organizational standards, patterns, frameworks, and best practices to develop test automation architectures and scripts, that enable the fulfilment of business strategies 
• Implement and support end -to-end DevOps framework 
• Ensure that delivered solutions are aligned to enterprise standards (Architecture, Operations, and Infrastructure) and of high quality while maintaining the required non-functional attributes such as performance, supportability, security, usability, reliability and stability 
• Actively troubleshoot any issues that arise during testing and production 
• Drive internal proof of concept initiatives 
• Implement guidelines, standards and procedures for databases and disaster recovery, high availability and reporting instances. 
• Maintain a deep understanding of cloud data architecture, transition strategies and computing and technology systems. 
• Keep eyes and ears open on a continuous basis to understand upcoming needs and addressing them proactively  
• Should keep abreast of upcoming trends in the industry & ensure platform is up to date 
• Be an active presence in meetings. Be available for project team and collaborators for in-person consultation. Build essential relationships. 

Experience: 

• Strong knowledge in Terraform 
• Strong knowledge of Linux 
• Experience with Shell/Python scripting 
• Hands on experience with Azure/AWS cloud solutions 
• Expert knowledge on Azure DevOps core and Big Data managed services, Ansible, Terraform, Kubernetes, Jenkins, Nexus, etc 
• Experience on Automation and Orchestrating work loads across multi cloud providers 
• Experience on working with CI/CD tools and source control such as GIT/SVN 
• Ideal candidate should have experience in both product development as well as services environments, designing and implementing DevOps platform architectures for analytical and BI needs in large organizations on Microsoft Azure 
• Demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment. 
• Must have at least 6 years of experience working as a DevOps Engineer. 
• Must have experience with Azure cloud platform. AWS experience is an advantage. 
• Experience with managing infrastructure of various ETL tools (preferably in Talend and Spark) and understanding of their tradeoffs is a must 
• Should be preferably Microsoft Certified 

Soft Skills: 

• Analytical Problem-Solving: Approaching high-level data challenges with a clear eye on what is important; employing the right approach/methods to make the maximum use of time and human resources. 
• Effective Communication: Carefully listening to management, data analysts and relevant staff to come up with the best data design; explaining complex concepts to non-technical colleagues.  
• Professional working proficiency in English Language. 
• Expert Management: Effectively directing and advising a team of data modelers, data engineers, database administrators and junior architects. 
• Industry Knowledge: Understanding the way your chosen industry functions and how data are collected, analyzed and utilized; maintaining flexibility in the face of big data developments.