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Sr. Devops Python Engineer
3 months ago
Applicants who fit the below Job Criteria will only be contacted by TeamUpShoot
Job Hoppers will be strictly rejected
Rest, we appreciate your interest and you will only be be contacted by TeamUpShoot if any other opportunity suitable is available with us
About Client
Global Consulting Company's Technology Consulting Division
Role:
SSE-DevOps Python
Experience: 5
years - 8
years ( Total Relevant Expereience }
Locations:
Bangalore
Industry:
IT Software / Software Services
Education :
: BE/BTech/MCA in computer science from a reputed college.
Notice Period:
Immediate Joiners
ONLY
CTC:
Max 14
LPA
The Role :
This position requires a blend of
DevOps expertise ,
Python development skills , and a
fundamental understanding of data engineering and machine learning .
The candidate should be proficient in
deploying and managing applications in a containerized environment
and be capable of
writing robust backend services using modern Python frameworks .
Additionally,
experience with data pipeline development
and a
basic grasp of ML concepts
will be advantageous.
What you should have:
DevOps :
Proficiency in Docker and Kubernetes
for containerization and orchestration.
Experience managing CI/CD pipelines and automating deployment processes .
Python Scripting :
Expertise in developing applications using FastAPI, Flask, or Django frameworks .
Ability to write efficient, reusable, and scalable code .
Coding :
Strong coding skills in Python .
Ensuring code quality and adherence to coding standards .
What You'll Do :
Develop, deploy, and maintain software applications using Python and relevant frameworks .
Implement and manage containerized applications using Docker and Kubernetes .
Manage CI/CD pipelines to ensure smooth deployment processes .
Collaborate with cross-functional teams to design, develop, and optimize data pipelines .
Maintain and enhance database systems, ensuring efficient data storage and retrieval .
Good to have :
Data Engineering :
Experience with databases and knowledge of ETL processes .
Designing, building, and maintaining data pipelines.
Machine Learning :
Basic understanding of machine learning concepts and implementation.
Working knowledge of ML frameworks and libraries.