Senior Analyst, SIEM & Automation, Information Security

Edwards Lifesciences — India-Pune

Edwards Lifesciences is expanding its global technology capabilities with the launch of a new IT Innovation Hub in Pune, India. The Hub strengthens the technology foundation that supports our business worldwide, working in close partnership with teams across regions to deliver reliable, high-quality solutions at scale. Designed as a long-term investment, the Pune Hub will advance newer digital capabilities such as automation, data, AI, and cloud, and will include roles spanning end user services, application development, and enterprise platform teams. Together, these teams will help Edwards operate more efficiently and accelerate innovation in support of our mission of advancing patient care. As an Edwards Sr. Analyst for Information Security, you will contribute with protecting Edwards organization, applications, and products by leading SIEM engineering, managing data pipelines and building automation use cases. Ideal candidates possess knowledge in data source onboarding, writing parsers and SOAR operations. If you have an innovative mindset and a strong desire to address security challenges through scalable automation and SIEM engineering – this role is for you. How will you make an impact: Lead SIEM engineering: deploy, configure, and continuously optimize the SIEM platform for performance, scalability, and reliable data availability Own the SIEM data layer – ingestion, parsing, normalization, and data modeling – ensuring logs are complete, well-structured, and queryable across the platform Design, build, and maintain log ingestion pipelines from cloud, on-prem, and SaaS sources into the SIEM platform Write and tune field extraction rules, parsers, and normalization logic (regex, Grok, CEF/LEEF, OCSF, ECS) Onboard new data sources end-to-end: connector configuration, schema mapping, field normalization, and data validation Partner with detection engineers to ensure data quality and completeness for use-case coverage Manage log volume for cost optimization, and d

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