Senior Information Security Analysts - job 1 of 2

Senior Information Security Analysts at American Express are responsible for providing analytical support for issue management and project assessment. They play a vital role in user access control and monitoring data analysis activities, along with developing and debugging complex code. Additionally, they evaluate and automate processes to enhance productivity and develop data analytic services for the enterprise.

To qualify for the Senior Information Security Analyst role at American Express, candidates must possess a Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related STEM field, along with 5 years of progressively responsible experience in data warehousing and analysis. Key experience should include working with data mining, monitoring large data sets, and utilizing relational databases.

Yes! The Senior Information Security Analyst position at American Express provides telecommuting options allowing you to work from anywhere in the U.S. This flexibility is designed to support our colleagues' work-life balance while maintaining productivity.

American Express offers a comprehensive benefits package for Senior Information Security Analysts, including competitive base salaries, bonus incentives, extensive medical and dental coverage, a 6% company match on retirement savings, parental leave, and free access to wellness centers. They prioritize the well-being of all employees and their families.

Yes, the salary range for the Senior Information Security Analyst role at American Express is between $152,859 and $190,000 annually. The final compensation will be determined based on several factors including experience and location.

As a Senior Information Security Analyst, it’s crucial to implement a multi-layered approach for securing sensitive data. This includes monitoring user access control, conducting data encryption, and performing regular audits. Always emphasize your ability to follow best practices to ensure data integrity and compliance with industry standards.

When asked about data warehousing experience, detail specific projects where you architected data warehouses. Discuss the technologies used, your methodologies in data management, and how you streamlined processes for better efficiency. Providing quantifiable results can strengthen your response.

My approach to problem-solving involves thorough analysis of the issue at hand, leveraging data-driven insights to understand root causes, and implementing effective solutions. I prioritize collaboration among team members to gather diverse perspectives that enhance the outcome.

Highlight tools such as MS SQL Server, Oracle Warehouse Builder, and ETL processes you’ve used in past roles. Explain how you utilized these technologies for monitoring and reporting, and how they contributed to improved business outcomes.

Provide a real-life example of a process you successfully automated. Discuss the initial challenge, the steps you took to automate it, and the improvements in efficiency or productivity that resulted from your initiative.

Compliance is crucial in data security. I routinely stay updated with the latest regulations, perform regular audits, and conduct training for the team to ensure collective adherence to data protection protocols.

Mention your experience in developing and debugging complex codes, and how you conduct code reviews. Emphasize your familiarity with programming languages that are security-focused and your understanding of security best practices in coding.

I believe in addressing conflicts early on by encouraging open dialogue among team members. My approach focuses on understanding different viewpoints and working collaboratively towards a solution that respects everyone’s input.

Data monitoring and reporting require careful strategy. I utilize a combination of real-time monitoring tools and scheduled reporting. This helps in quickly identifying anomalies and conducting in-depth analyses when necessary.

Discuss your hands-on experience with extracting, transforming, and loading data using SQL Server or other tools. Explain how you optimized these processes to ensure data accuracy and availability for analytical use.