Cloud Support And Devops Engg Job in Maestro Placement Consultancy Services

Job Responsibilities:

The Cloud support & Architectwill be responsible for:

• Set up a cloud solution environment
• Plan and configure a cloud solution
• Deploy and implement a cloud solution
• Ensure successful operation of a cloud solution
• Configure access and security
• Automating the build and configuration of IaaS based solutions in Google & AWS Cloud Platform
• Write scripts and automation using Perl/Python/Groovy/Java/Bash
• Configure and manage data sources like MySQL, Mongo, Elasticsearch, Redis, Cassandra, Hadoop, etc
• Manage source control including SVN and GITLAB
• Build the process required for optimal extraction, transformation, and loading of data from a wide variety of data sources to google cloud
• Analyze, explore and select the appropriate tools for data migration and transformation.
• Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.

Functional Skills: -

• Working knowledge of Google Cloud Platform & AWS cloud platform
• Good understanding of cloud design considerations and limitations in the areas of virtualization and global infrastructure, distributed systems, load balancing and networking, massive data storage and processing.
• Prior experience working with: container technology such as Docker, version control systems (Gitlab), build management and CI/CD tools (gitlab), and monitoring tools (App Dynamics, stack drive etc.)
• A general understanding of networking principles and protocols such as IP subnetting, routing, DNS, etc.
• Proficient in a modern scripting language (preferably Python)
• Expert knowledge of Application Performance Monitoring tool like Dynatrace, Splunk, Gomez, Coradiant, and Tealeaf
• Experience with infrastructure configuration management tools such as Puppet and Chef.
• Unix/Linux power user.

Technical Skills-

• Major Database/Data Warehouse tools:
• Google Bigquery( to build analytical datasets).
• Google Storage ( File system and this is the port of entry for all the data that lift from bastion as per the standard)
• Google Bigtable & DataStore for application logs and stats.
• Oracle runs in google engine as a Controller for Job scheduling.

Engines:

• Google App engine (Data processing)
• AWS Lambda
• Compute Engine (Data processing and Application platform)

Tools:

• GITLAB(To build a pipelines and CICD)
• Concourse - CICD
• FLOW (inbuilt tool for automated deployment)
• Google Dataflow (Data pipeline to read from Pub/Sub).
• Google Pub/Sub ( as Queues in google cloud)

Languages: (in order of precedence)

• Python
• Java
• Groovy
• Shell scripting