Cyber Threat Content Analyst
Location: , United States
Date Posted: Jan 5, 2022
Securonix provides the Next Generation Security and Information Event Management (SIEM) solution. As a recognized leader in the SIEM industry, Securonix helps some of the largest organizations globally to detect sophisticated cyberattacks and rapidly respond to these attacks within minutes. With the Securonix SNYPR platform, organizations can collect billions of events each day and analyze them in near real time to detect advanced persistent threats (APTs), insider threats, privilege account misuses and online fraud.
Securonix pioneered the User and Entity Behavior Analytics (UEBA) market and holds patents in the use of behavioral algorithms to detect malicious activities. The Securonix SNYPR platform is built on big data Hadoop technologies and is infinitely scalable. Our platform is used by some of the largest organizations in the financial, healthcare, pharmaceutical, manufacturing, and federal sectors.
We are looking for a savvy Data Engineer to join our growing team of analytics experts with hands-on experience to work on cutting edge technology. The hire will be responsible for expanding and optimizing our data pipeline architecture, as well as optimizing data flow and collection for cross functional teams which will impact the overall UEBA (User Entity Behavior Analytics) use cases. An ideal candidate is an experienced data pipeline builder and data wrangler who enjoys optimizing data systems & building them from the ground up and will be responsible for out-of-the-box threat use case delivery. The Data Engineer will support our software developers, SIEM engineers, data analysts and work with the Threat Lab data scientists on data parsing, use case delivery and will ensure optimal delivery architecture is consistent throughout ongoing projects. They must be self-directed and comfortable supporting the data needs of multiple teams, systems and products. The right candidate will be excited by the prospect of optimizing or even re-designing our company’s data architecture to support our next generation SIEM (Security Information and Event Management).
- Implement/develop out-of-the-box parsers/connectors and responsible for net new development of parsers including enhanced categorizations and use cases.
- Data validation program for supported data sources and responsible for quality assurance
- Content validation for all the out-of-the-box use cases and threat models
- Implementation, validation of supported dashboards / reports and net new development of custom dashboards/reports
- Coordinate with product management & engineering for troubleshooting connector integration issues for various products
- Work with data and analytics experts from Securonix Threat Labs to strive for greater functionality in our data systems and streamline supported data parsing and use case configurations
- Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
- Work with stakeholders including the Executive, Product, Data and Design teams to assist with data-related technical issues and support their data infrastructure needs.
- Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.
- Strong experience in regex implementation and parser creation (must have)
- Good amount of experience in SVN, Git or any other version control tool (must have)
- Intermediate working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working with a variety of databases.
- Experience building and optimizing ‘big data’ data pipelines, architectures and data sets.
- Experience performing root cause analysis on internal and external data and processes to answer specific business questions and identify opportunities for improvement.
- Strong analytic skills related to working with structured and unstructured datasets.
- Build processes supporting data transformation, data structures, metadata, dependency and workload management.
- A successful history of manipulating, processing and extracting value from large disconnected datasets.
- Strong working knowledge of parser management, stream processing, and highly scalable ‘big data’ data stores.
- Strong product management and organizational skills.
- Experience supporting and working with cross-functional teams in a dynamic environment.
- 1-3 years experience in the Data Engineering, who has attained a Graduate (Masters) degree in Computer Science, Information Systems or Cyber Security field OR 3+ years of experience in the Data Engineering with a Bachelor's degree in Computer Science, Information Systems or Cyber Security field
- 1-3 years or more of hands-on working experience in engineering development and SIEM solution deployment
- They should also have experience using the following software/tools:
- Experience with relational SQL databases
- Experience with object-oriented/object function scripting languages (1 of the following): Python, Java or Bash scripting.
- SVN / Git or any version control tool
- Experience with NoSQL databases - REDIS.
- Experience with object-oriented/object function scripting languages (1 of the following): Python, Java, Bash.
- Experience with big data tools: Hadoop, Spark, Kafka, etc.
- CISSP / CEH certified or any certification related to SIEM / UEBA deployment
- Leadership certification and/or awards attained for leadership skills
- Working knowledge of cloud technologies such as Amazon, Azure and Google
- Good understanding of log collection and forwarding technologies such as Syslog-NG, rsyslog, Nxlog, Windows Event Forwarding
- Experience integrating endpoint security and host based intrusion detection solutions
- Experience with networking technologies such as Wireshark, PCAP, tcpdump