Cyber Database Architect

Title: Cyber Database Architect

Position Type: Contract

Location: Remote

Update: They are focusing on four key areas for this role with varying degrees of importance assigned to each area depending on the position:

• Data science ETL scripting cyber domain knowledge and Splunk expertise
• Genuine ETL scripting experience beyond the use of prebuilt scripts

For the initial interview process the client will be incorporating coding challenges and questions into our interview process.

Description:

We are seeking a Cyber Database Architect responsible for developing and implementing proper architecture and engineering safeguards around cyber security data. The architect is expected to have a deep knowledge of a broad range of information and physical security controls to protect data stores (potentially including the data the data applications or stored functions the data systems the data servers and the associated network links) against compromises of their confidentiality integrity and availability. Performs requirements analysis and developing strategies and solutions for cyber security risk and information governance. Helps identify and evaluate gaps and potential areas of security exposure.

Duties and responsibilities:

Design develop build analyze and evaluate unstructured data stream from varies data sources to include database modeling and design relational database architecture metadata and repository creation and configuration management.

Defining and overseeing database organizations standards controls procedures and documentation.

Providing technical consulting in the definition design and creation of a data base environment.

Advising applications development staff and users on databased solutions to business problems data architectures database management system facilities and capabilities and the operation and tuning of data bases.

Ensuring economic and efficient availability of data within adequate safeguards.

Designing and implementing databases with respect to access methods access time batch processes device allocation validation checks organization protection and security documentation and statistical methods.

Using data mapping data mining and data transformational analysis tools to design and develop databases.

Determining data storage and optimum storage requirements.

Preparing system requirements source analysis and process analyses and design throughout the database implementation.

Basic qualifications:

Bachelors degree and 8 years of experience Masters degree and 6 years of experience or 12 years of experience in lieu of a degree

Minimum 46 years of experience in building out Data Warehouses/ Data models / Data repositories and/or Data Lakes

Minimum 46 years of experience in leveraging preload data pull from a mature data model

Minimum of 46 years of experience in creating consolidated data sets that conforms to a Common Information Model made up of senor tool data sources thats already aggregated together & is also already searchable

Minimum of 3 years transforming already good data (data that has been normalized) into the format needed for ingestion by Xacta.IO and CDM Elastic

Minimum 4 years of experience in creating data pipelines to allow transfer of data from data source to I/O through Splunk

Minimum 4 years of experience creating data Information Identifiers/tag Identifies within data models

Minimum 4 years of experience working with data source sensor tools such as Tanium Nessus McAfee firewalls networking equipment to collect data points

Minimum 2 years of experience with creating data tattoos and with mapping data back to the tattoo as defined

Minimum 3 years of experience with taking Production ready data and include it in Cyber Risk data model(s)

Must be able to obtain and maintain a US Public Trust clearance.

Preferred qualifications:

Exceptional technical writing skills

Ability to communicate complex data in a simple actionable way

Ability to visualize data in the most effective way possible for a given project or study

Analytical and problemsolving skills

Experience with machine learning and AI

Familiarity with data management tools

Ability to work independently and with team members from different backgrounds

Excellent attention to detail.