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The Associate Data Analyst supports the development and enhancement of cybersecurity metrics and AI-driven analytics within the organization. This role works as part of the Security Automation, AI, and Analytics (SA3) team and is responsible for developing, maintaining, and enhancing Amgen's Cybersecurity Metrics and Analytics platform, to support strategic, operational, and tactical reporting for both internal and external stakeholders. The analyst will assist in curating cybersecurity data in the Enterprise Data Lake, enabling effective measurement and communication of security posture to internal and external stakeholders. In collaboration with cybersecurity teams, the Associate Data Analyst will also contribute to the implementation of automation aimed at strengthening threat detection and improving overall security operations.
Job Responsibility:
Support Cybersecurity and Digital Trust (CDT) metric reporting processes, ensuring accuracy and stakeholder alignment
Architect and deliver advanced dashboards that integrate strategic, operational, and tactical cybersecurity metrics using tools such as Tableau, Power BI, Spotfire, and R
Drive the design and implementation of on-demand reporting solutions that support high-impact decision-making across business and technical teams
Guide data discovery initiatives to identify reporting enhancements and develop scalable, optimized data storage solutions
Serve as a liaison with Amgen's Security Metrics and Analytics team and stakeholders to evaluate and incorporate emerging technologies, including AI and machine learning
Align data and analytics initiatives with the program's strategic vision, ensuring adoption of interoperable, cost-effective, and authorized technologies such as cloud platform
Collaborate with cross-functional teams including data analysts, data engineers, and data scientists to define requirements, translate business needs, and enhance cyber defense capabilities
Establish and maintain comprehensive documentation of metrics, data workflows, and reporting processes, ensuring knowledge transfer and audit readiness
Develop and maintain robust operational scripts, reusable code libraries, and data structures that strengthen security across complex, global computing environments
Engineer and operate automation scripts, test environments, and infrastructure-as-code solutions in support of advanced security objectives
Operate with initiative, effectively managing priorities in a dynamic environment with minimal oversight
Demonstrate strong leadership in communication, organization, and stakeholder engagement with a customer-focused mindset.
Requirements:
Bachelor's degree and 2 to 6 years of experience with one or more analytic visualization tools or languages (e.g., Tableau, Power BI, etc.)
Hands-on experience with data analytics platforms and tools such as Tableau, Power BI, etc.
Proven ability to influence decision-making by clearly communicating complex security risks and data insights to both technical and non-technical stakeholders
Effective communicator with experience presenting to senior leadership and facilitating discussions with medium to large audiences
Clear understanding of relational and dimensional database modeling with the ability to design and support scalable data structures.
Nice to have:
Experience with Databricks
Strong programming skills in both compiled (e.g., C, C++) and interpreted languages (e.g., Python, Ruby), with practical experience in high-level languages such as Java, C#, and Visual Basic
Proficient in AI/ML concepts and tools, with a foundational understanding of algorithms and frameworks used for advanced analytics and anomaly detection
Demonstrated success working within Agile and DevOps teams, with practical experience in SCRUM practices and collaborative, iterative delivery
Skilled in DevOps and infrastructure automation using tools such as Ansible, Chef, Puppet, Docker, and Jenkins to build, test, and deploy cloud-based environments
Familiar with BI technology stacks and data analytics domains, with the ability to adapt to evolving enterprise architectures
Demonstrated adaptability and continuous learning in adopting new technologies, particularly in the areas of cloud, analytics, and cybersecurity.