• Citizen

• Full Time

• Direct Hire

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 9th Dec 2022

Someone who can help client to build scalable, reliable, and secure Data analytic solutions.

Technologies you will get to work with: -

 

1.Azure Databricks

2.Azure Data factory

3.Azure DevOps

 

4.Spark with Python Scala and Airflow scheduling.

 

What You will Do:-

 

As a DevOps engineer you will work as an integral part of our Cloud DevOps team for a Retail client. The ideal candidate has extensive DevOps knowledge and experience and has previously been part of a DevOps team running an analytical ecosystem in modern cloud-based big data systems in a fast-paced, agile environment.

The Specific Focus for The DevOps Engineer Is On Processing Engine Development As Well As The Design, Development, Automation And Optimisation Of Its Usage In Client s Analytic Ecosystem:

 

Liaise in a geographically dispersed team by co-location with our client across globe.

Participate in a continuous delivery pipeline to fully automate deployment of the highly available cloud platform that supports multiple teams/projects

Build tools for deployment, monitoring and operations. Troubleshoot and resolve issues in our development, test and production environments

Strong working experience in CI/CD processes

Work with platform architects on software and system optimisations, helping to identify and remove potential performance bottlenecks

Stay up-to-date on relevant technologies, plug into user groups, understand trends and opportunities to ensure we are using the best possible techniques and tools

Understand, implement, and automate security controls, governance processes, and compliance validation

Design, manage and maintain tools to automate operational processes

 

Required Technical and Professional Expertise:

 

Professional programming experience and hands-on experience in building modern data platforms/pipelines.

Programming languages: Scala, Java, Python is plus

Frameworks: Spark, Hadoop, Hive, Kafka

Databases: Azure Synapse, NoSQL, Strong in Relational databases

Data pipelining: Azure Data factory, ELT

Scheduling: Airflow

Cloud: Azure Stack, Azure DevOps, Azure Databricks

Experience in Kubernetes, Docker, and Virtualisation

DevOps: Experience in Agile, CI/CD

Previous experience gained in mid-size/large, international companies