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Data Analyst

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Employee will be responsible for the acquisition, management, and quality control of data to support the Next Gen Cybersecurity Analytics project and the ongoing work of the cybersecurity data science team. This individual will be a key member of the project team who is expected to take primary responsibility for adding ~2 dozen new data sources into a Hadoop data lake, creating proactive data QC processes, and ensuring that data is made accessible as required for the data science team to consume.
Key responsibilities include:
• Management, organization, acquisition of data in the cybersec data lake
• QC and data quality management
• Coordination between data owners, app support, and ETL developers to acquire new log sources required by the data scientists
• Collaborate with data scientists to identify and acquire auxiliary information (ie user data, asset inventories, 3rd party sources, etc)
• Design data acquisition, storage, and organization to be performant in a Hadoop environment
• Implement tools & processes to ensure high level of ongoing data quality needed to support cybersecurity operations
Required skills:
• Proficient in at least one of the following: python, perl, Java, Linux shell scripting
• Experienced Linux user
• Working knowledge of cybersecurity and networking concepts at a level sufficient to effectively QC data
• Past roles managing high volume technical data for scientific computing or big data applications
• Experienced with Hadoop platform and associated toolset (Hive/Impala, Pig, Spark)

Experience with Linux as a user/power user: 10+ years
Past work experiences involving management of technical data: 5-10 years
Linux shell scripting: 5-10 years
Python, perl, or Java programming: 5-10 years
Hadoop (including at a minimum Pig and Hive/Impala; Spark strongly preferred as well): 2-5 years


The following skills are desirable but not required:
• Data visualization with Spotfire
• ETL development experience

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