Senior Detection Engineer
Key Skills for This Role
Full Job Posting
Essential requirements
- At least eight years of cybersecurity experience, including four or more years in detection engineering, threat detection, or SOC engineering.
- Experience designing or leading a detection engineering function in a large or regulated organization.
- Expert hands-on Microsoft Sentinel experience, including KQL, analytics rules, workbooks, watchlists, and automation.
- Expert hands-on IBM QRadar experience, including AQL, custom rules, building blocks, DSMs, and reference sets.
- A track record turning cyber threat intelligence into operational detections.
- In-depth knowledge of MITRE ATT&CK, D3FEND, Cyber Kill Chain, Diamond Model, Pyramid of Pain, and NIST CSF.
- Experience with detection-as-code, Git-based version control, and CI/CD pipelines.
- Knowledge of attacker tradecraft across Windows, Linux, Azure/M365, identity, and network environments.
- Scripting skills in Python and/or PowerShell.
Desirable experience and certifications
- Banking or financial services experience is highly desirable.
- Experience with Sigma, YARA, threat intelligence platforms, purple teaming, adversary emulation, red team collaboration, Microsoft Defender XDR, EDR, or SOAR is desirable.
- Threat hunting or cyber threat intelligence experience is desirable.
- GIAC certifications such as GCDA, GCIA, GCTI, GCIH, or GREM are preferred.
- Microsoft SC-200, IBM QRadar certifications, CISSP, OSCP, or equivalent are preferred.
Education
- Bachelor's degree in Computer Science, Information Security, Engineering, or a related field, or equivalent professional experience.
Key competencies and role contribution
- Build a detection engineering function from the ground up and align it with business risk.
- Develop detections across Sentinel and QRadar with expert technical depth and an intelligence-informed approach.
- Communicate detection posture clearly to executives, auditors, and regulators.
- Mentor colleagues and promote sound engineering practices.
- Make data-driven decisions supported by meaningful metrics.
- Provide steady, structured leadership during significant incidents.
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