11 дней назад
Senior Data Protection Analyst (DLP)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior Data Protection Analyst (DLP): Analyzing data security incidents, endpoint forensic events, and Cyberhaven’s Data Detection and Response platform with an accent on insider-threat detection, DLP analytics, and customer data-risk strategies. Focus on refining policies and datasets, eliminating false positives, conducting forensic analysis, and automating investigations with SQL, APIs, and scripts.
Location: US Remote or Mexico
Company
builds data security products that trace the full lifecycle of data and adapt protection to changing work contexts, with a focus on protecting agentic enterprise workflows.
What you will do
- Provide insight into DLP analytics and related customer issues.
- Analyze Data Detection and Response platform events to improve policies, incidents, and alerts.
- Refine datasets and DLP policies as customer data-risk strategies and business needs evolve.
- Prepare and present analysis summaries and reports to internal stakeholders.
- Reduce noise and false positives to improve detection accuracy.
- Conduct forensic analysis of people, groups, and non-sanctioned data egress destinations.
Requirements
- 5+ years of experience with data protection or adjacent security tools such as EDR, SIEM, or SOAR.
- 2+ years of experience in insider threat or information security.
- Strong understanding of endpoint protection practices and incident mitigation workflows.
- Experience with DLP, insider threat, CASB, and sensitive-data handling controls.
- Technical experience across macOS, Linux, Windows, AWS, GCP, and Azure.
- SQL, dashboard development, XML-based DLP rules, scripting, and API usage.
Culture & Benefits
- Remote work is available from the US or Mexico.
- Work with a global, customer-centric team focused on cloud security and emerging technology.
- Join a company building data security for the agentic enterprise.
- Recruiting workflows may use AI-powered tools for scheduling, note-taking, and automation; candidates can opt out of AI-assisted interview note-taking.
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