Mid Level Cloud Dev Ops- India
About Cognify Analytics
At Cognify Analytics, we’re driven by a single belief: that data and AI should be accessible and transformative for every organization. Founded by a team of ex-Google and Meta technologists, we specialize in delivering cutting-edge analytics and cloud solutions to companies around the globe. Whether it’s deploying machine learning models, optimizing cloud infrastructure, or guiding enterprise migrations—our mission is to turn complex data challenges into real-world impact.
The Role
We’re seeking a Mid-Level Cloud/DevOps Engineer to independently design, build, and operate cloud infrastructure and DevOps workflows on AWS and Azure. In this role, you will own key infrastructure components end to end, drive CI/CD maturity, manage containerized and serverless workloads, and collaborate with development and data teams to ensure reliable, secure, and cost-optimized cloud operations. You will also support cloud migrations, build automation frameworks, and integrate AI-powered tools into operational workflows.
What You’ll Do
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Design, provision, and manage production cloud infrastructure on AWS and Azure using Terraform, CloudFormation, CDK, Bicep, or Pulumi.
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Build and maintain robust CI/CD pipelines for application and infrastructure deployments using GitHub Actions, GitLab CI, Jenkins, AWS CodePipeline, or Azure DevOps.
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Deploy and manage containerized workloads on Amazon ECS, EKS, or Azure Kubernetes Service (AKS), including service mesh and auto-scaling configurations.
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Implement serverless architectures using AWS Lambda, Step Functions, API Gateway, EventBridge, Azure Functions, and Logic Apps.
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Support and execute cloud migration projects, ensuring scalability, security, and minimal downtime during transitions.
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Develop and maintain Django-based and Python back-end applications integrated with cloud-native services such as RDS, DynamoDB, ElastiCache, S3, and SQS.
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Implement infrastructure monitoring, alerting, and observability using CloudWatch, Azure Monitor, Prometheus, Grafana, Datadog, or OpenTelemetry.
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Automate operational workflows using Python, Bash, Go, or PowerShell and build self-healing infrastructure patterns.
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Enforce security best practices including IAM, VPC design, WAF, secrets management (Secrets Manager, Vault), encryption, and compliance controls.
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Optimize cloud costs through reserved instances, savings plans, right-sizing, and FinOps practices.
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Collaborate with development, data engineering, and ML teams to support application deployments, data pipelines, and AI/ML workloads.
What We’re Looking For
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Bachelor’s or Master’s degree in Computer Science, Information Technology, or a related field.
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3–5 years of professional experience in cloud engineering, DevOps, or site reliability engineering with production responsibility.
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Strong hands-on experience with AWS services (EC2, S3, RDS, Lambda, VPC, ECS/EKS, CloudFormation, IAM) and/or Azure services (VMs, AKS, App Service, Functions, ARM/Bicep).
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Proficiency with infrastructure-as-code tools: Terraform (strongly preferred), CloudFormation, CDK, or Pulumi.
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Experience building and managing CI/CD pipelines with GitHub Actions, GitLab CI, Jenkins, or cloud-native pipeline services.
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Working knowledge of Docker, Kubernetes, and container orchestration in production environments.
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Strong scripting skills in Python, Bash, or Go for automation and tooling.
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Solid understanding of networking (VPC, subnets, load balancers, DNS, CDN), security (IAM, RBAC, encryption), and compliance in cloud environments.
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Experience with monitoring and observability tools: CloudWatch, Prometheus, Grafana, Datadog, or equivalent.
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Familiarity with Agile methodologies and collaborative development workflows.
Preferred Qualifications
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AWS Solutions Architect Associate/Professional, AWS DevOps Engineer Professional, or AZ-104/AZ-400 certification.
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Experience with Django or FastAPI applicat