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Job Description

Description :


We are seeking a DevOps Engineer with strong experience in cloud infrastructure, automation, and CI/CD, along with hands on exposure to React frontend applications and Python/PySpark-based data or backend workloads. The ideal candidate will support end to end application and data pipeline deployments in a scalable and reliable environment.


Key Responsibilities :


- Design, implement, and maintain CI/CD pipelines for React, Python, and PySpark applications


- Deploy and manage React frontend applications and Python/PySpark backend or data processing jobs


- Automate infrastructure provisioning using Infrastructure as Code (IaC) tools


- Manage and optimize cloud infrastructure (AWS / Azure / GCP)


- Build, deploy, and manage containerized applications using Docker and Kubernetes


- Support data pipelines and batch/stream processing using PySpark


- Ensure system reliability, scalability, performance, and security


- Implement monitoring, logging, and alerting solutions


- Troubleshoot deployment and production issues across environments


- Collaborate with development and data engineering teams


- Apply DevSecOps best practices across pipelines and infrastructure


- Document architecture, deployment processes, and operational runbooks


Required Skills & Qualifications :


- Bachelors or advanced Degree in a related technical field


- 5 to 8+ years of experience in DevOps / Infrastructure Engineering


- Strong experience with cloud platforms (AWS preferred; Azure/GCP acceptable)


- Hands?on experience with CI/CD tools (Jenkins, GitHub Actions, GitLab CI, Azure DevOps)


- Experience with Docker and Kubernetes


- Proficiency in Python for automation and backend support


- Hands?on experience with PySpark for data processing or analytics workloads


- Working knowledge of React application build and deployment processes


- Experience with Infrastructure as Code (Terraform, CloudFormation, ARM)


- Strong scripting skills (Bash, Python)


- Familiarity with monitoring/logging tools (Prometheus, Grafana, ELK, Datadog, etc.)


Preferred Qualifications :


- Experience with big data platforms (EMR, Databricks, Spark on Kubernetes)


- Knowledge of microservices architecture


- Experience with DevSecOps and security scanning tools


- Familiarity with data orchestration tools (Airflow, Step Functions)


- Cloud certifications (AWS / Azure / GCP)


- Experience working in Agile/Scrum environments


Soft Skills :


- Strong communication and collaboration skills


- Ability to work across DevOps, frontend, backend, and data teams


- Ownership mindset and proactive problem's olving attitude


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