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Big Data Security Engineer

Employer
Barclay Simpson.
Location
South East of England
Salary
Competitive
Closing date
4 May 2021

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Job Description
This international FTSE100 company seeks a Big Data Security Engineer to join it's growing information security engineering division. Initially, the role will be based from home and post-Covid, you will work 2 days a week from home and 3 days a week from the office in the South East (Surrey).

The firm seeks an Information Security Engineering Specialist with strong technical expertise in Big Data, who is interested in joining this new squad to help build and operate this service and the underlying products. As a key member of this team, you will be working as part of the small empowered, customer-centric squad to deliver this consolidated, easy to use data platform for reporting and analytics.

In this role, you will play an integral role in building the team's skillset, to grow and deliver agile and commercially cost-effective solutions for information security engineering. You will support information security & risk activities, and facilitate the delivery of security solutions to projects across design, building and execution phases. You will also Implement and apply relevant operating processes and procedures, to ensure activities adhere to standards, reporting effectiveness of security procedures and making recommendations to drive implementation.

The successful candidate will have some experience of:
• Build logging and analytics capability for Software Defined Storage for operational checks
• Build Azure Resource Manager (ARM) templates for deployment of data products into production
• Creation of build and release pipelines for all SDS deployments
• Patching of VMs and automation of these processes
• Assist with build of flexible data APIs that support the ingestion, or the consumption needs of the data lake and its customers.
• DevOps on Azure and AWS cloud environments.
• Scripting Languages: Python, C#, PowerShell (at least one of them)
• Data Management experience e.g. large volume data handling and data wrangling
• Experience in automated data driven testing
• DB Programming: relational dbs (SQL), nonrelational (NoSQL, MongoDB, Cassandra)

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