Data Engineer - DevOps

Fractal Analytics · Bengaluru

  • Experience4–8 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Levelmid
  • Posted2 Sept 2026
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About Fractal Analytics

Fractal Analytics is hiring in Bengaluru in technology software. This role looks for around 4+ years of experience.

Skills

  • AWS
  • Azure
  • Python
  • MLflow
  • Kubernetes
  • Terraform
  • AWS SageMaker
  • AWS Lambda
  • AWS Step Functions
  • Ansible
  • CloudFormation
  • Jenkins
  • Groovy
  • Docker
  • Amazon ECS
  • Amazon ECR
  • Infrastructure as Code
  • IaaS
  • PaaS
  • SaaS
  • serverless architecture
  • cloud computing
  • cloud-native applications
  • AI
  • machine learning

The role

A cloud DevOps engineer at a technology software company designs and operates scalable cloud-native applications using AWS, Azure, and Kubernetes, with expertise in MLflow and infrastructure automation. The role builds continuous integration and continuous deployment pipelines and supports reliable serverless platforms.

Full job description

Responsibilities:

Analyze and translate business requirements into scalable and resilient design.

Own parts of the application and continuously improve them in an agile environment.

Create high-quality, maintainable products and applications using best engineering practices.

Pair with other developers and share design philosophy and goals across the team.

Work in cross-functional teams (DevOps, Data, UX, Testing, etc. ).

Build and manage fully automated build/test/deployment environments.

Ensure high availability and provide quick turnaround to production issues.

Contribute to the design of useful, usable, and desirable products in a team environment.

Adapt to new programming languages, methodologies, platforms, and frameworks to support the business needs.

Requirements:

Degree in computer science or a similar field.

Four or more years of experience in architecting, designing, developing, and implementing cloud solutions on AWS and/or Azure platforms.

Technologies: Python, Azure, AWS, MLflow, Kubernetes, Terraform, AWS SageMaker, Lambda, and Step Functions.

Development experience with configuration management tools (Terraform, Ansible, CloudFormation).

Developing and maintaining continuous integration and continuous deployment pipelinesJenkins Groovy scripts.

Developing containerized solutions and orchestration (Docker, Kubernetes, ECS, ECR)

Experience with serverless architecture, cloud computing, cloud-native applications, scalability, etc.

Understanding of core cloud concepts like Infrastructure as Code, IaaS, PaaS, and SaaS.

Relevant certification of Azure or AWS preferred.

Troubleshooting and analytical skills.

Knowledge of AI and ML technologies, as well as ML model management context

Strong verbal and written communication: should be able to articulate concisely and clearly.