Live opening · Posted 27 days ago

Data Engineer - DevOps

Fractal Analytics · Bangalore
Instahyre 4-8 yrs
You are 27 days behind. JobBeeper subscribers saw this role while it was still new.

At a glance

The key details from the original listing.

Posted 27 days ago
CompanyFractal Analytics
LocationBangalore
Experience4-8 yrs
SourceInstahyre
Listed27 days ago

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About the role

Description supplied by the original job listing.

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.

Experience
4-8 yrs

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