Data Engineer - Security Analytics

Job description

Data Engineer - Security Analytics

  

Job Description:

   

Hewlett Packard Enterprise (HPE) is seeking a highly-motivated, Cyber Security Data Science Engineer who can join the Global Cyber Data Analytic team based in Galway, Ireland.

We are looking for an experienced data science engineer who likes challenges, learning new things and is able to acquire new technologies quickly.

We used Scrum based lightweight development process with peer code reviews and DevOps practice. The candidate will be responsible for the design, development, implementation and engineering support for an internally developed large scale security data analytic platform that processes vast amount of cyber security data from various devices and systems.  

We offer an exciting and fun work culture, driving innovation, collaboration, and growth.

Primary Responsibilities:

·  Work closely with internal Cyber Security teams to understand processes and user requirements
·  Create efficient large scale data pipeline to parse, transform and correlate data from various sources using Big Data technologies
·  Design data access API solutions and build Machine Learning data model workflow 
·  Troubleshoot performance and data related operational issues to ensure data availability

Education and experience:

·  Typically a Bachelor’s degree or equivalent experience and a minimum of 7 years of related experience or a Master’s degree and a minimum of 5 years of experience 

Required Qualifications:

·   Strong functional or object oriented language experience, 4 years of Scala or Java preferred
·   Strong experience with Linux system environment with scripting skills (Python, Bash etc.)
·   Good understanding of network protocols such as TCP/IP
·   Experience with containerization tools, i.e. Docker, Docker Swarm, Kubernetes
·   Experience with Continuous Integrations tools, i.e. GitLab, Jenkins
·   Experience with build systems, i.e. Gradle (bonus) or Maven
·   Experience with Supervised, Semi-supervised and Unsupervised Learning
·  Experience with Classification and Regression, Active and Reinforcement Learning, Feature Design and Engineering, Model Training and Evaluation
·  Experience with Data Mining, Optimization, Anomaly Detection and Statistics

Bonus:

·  Working experience with distributed computing (Hadoop, Spark and Kafka)
·  Knowledge of Neural Networks, Decision Trees, Support Vector Machines, Regression Analysis, Bayesian Networks, Genetic Algorithms
·  Experience with open-source tools for the above
·  Knowledge of  Micro services architectures, RESTful micro services

Job:
Information Technology

Job Level:
Expert

    

Hewlett Packard Enterprise is EEO F/M/Protected Veteran/ Individual with Disabilities.

   

HPE will comply with all applicable laws related to the use of arrest and conviction records, including the San Francisco Fair Chance Ordinance and similar laws and will consider for employment qualified applicants with criminal histories.