Goldman Sachs Technology Risk is leading threat, risk analysis and data science initiatives
that are helping to protect the firm and our clients from information and cyber security risks. Our team equips the firm with the knowledge and tools to measure risk, identify and mitigate threats and protect against unauthorized disclosure of confidential information for our clients, internal business functions, and our extended supply chain.
SECURITY INCIDENT RESPONSE TEAM (SIRT) supports and enables a comprehensive technical Cyber Defense program for the firm while increasing awareness of current and potential Cyber Threats. Works across the organization to operate efficiently, provide technical
investigative support and mitigate threats to the firm.
Do you enjoy solving challenging puzzles? Protecting critical networks from cyber-attacks? Designing and integrating state-of-the-art technical solutions? A position as a Security Data Engineer on Goldman Sachs Threat Management Center lets you do all this and more:
HOW YOU WILL FULFILL YOUR POTENTIAL
Design and develop data ingest and transform processes
Engineer streaming data processing pipelines
Drive adoption of Cloud technology for data processing and warehousing
Engage with data consumers and producers in order to design appropriate models to suit all needs
Apply latest technologies in machine learning, data mining, and predictive analytics to correlate the big datasets and events, and derive dynamic cybersecurity rules.
Collaborate with a global team to continually operate and improve a world-class cyber program by driving the uplift of sensory tools, detection tuning, and access to data sources to increase detection effectiveness by applying data analytics.
Participate in a 24x7 coverage model to prevent and remediate security threats against Goldman Sachs global business network.
SKILLS AND EXPERIENCE WE ARE LOOKING FOR
5+ years of relevant work experience in a team-focused environment
Bachelors degree (Masters preferred) in a computational field (Computer Science, Applied Mathematics, Engineering, or in a related quantitative discipline)
Working knowledge one or more programming languages (Python, Java, C++, C#, etc.)
Extensive knowledge and proven experience applying domain driven design to build complex business applications
Deep understanding of multidimensionality of data, data curation and data quality, such as traceability, security, performance latency and correctness across supply and demand processes
In-depth knowledge of relational and columnar SQL databases, including database design
Excellent communications skills and the ability to work with subject matter experts to extract critical concepts
Ability to multi-task and prioritize work effectively
Independent thinker, willing to engage, challenge or learn
Highly motivated self-starter who can provide thought leadership in big data analytics
Strong work ethic, a sense of ownership and urgency
Strong analytical and problem solving skills
Responsive to challenging tasking.
Ability to document and explain technical details in a concise and understandable manner.
Strong sense of ownership and driven to manage tasks to completion.
Financial Services industry experience
Previous work experience in Cyber Security field is a plus.
Experience with the Hadoop eco-system (HDFS, Spark)
Experiance with cloud based big data platforms such as AWS or Google a plus.