# Security Incident Response Engineer

**Company:** [Stripe](https://hotfix.jobs/companies/stripe)
**Location:** Remote
**Role:** Security Engineering
**Experience:** 3+ years
**Skills:** Python, SQL, Log Analysis, Network Security, Digital Forensics, Incident Response, Databricks, Jupyter, Trino, Pyspark, pandas, scikit-learn, Osquery, Splunk, SIEM
**Posted:** 2026-09-10

> Build and improve security analytics, detection, and incident response capabilities by analyzing telemetry, investigating threats, and developing scalable behavioral models and pipelines. Requires 3+ years of security analytics experience, strong Python and SQL skills, and expertise in incident response and forensics.

## Job Description

## Responsibilities
- Analyze and investigate threats or activities occurring on client devices.
- Develop requirements for detection models and enhance existing systems.
- Collect, transform, and ingest raw data from disparate sources into threat detection pipelines.
- Streamline incident response capabilities, tooling, and processes.
- Work cross-functionally with security engineering and data science teams to analyze security event data at scale and protect networks, systems, and data.
- Provide actionable insights to identify, prevent, detect, and respond to anomalous or potentially malicious user and entity activity.
- Serve as a subject-matter expert and primary contact for Security Analytics and Detection programs and company-wide security initiatives.
- Lead projects, mentor teammates, and champion quality standards.

## Requirements
- 3+ years of experience analyzing large datasets to solve problems and/or building behavior-based security models.
- B.S. or M.S. in Computer Science or a related field, or equivalent experience.
- Expert knowledge of Python and SQL; familiarity with other programming languages.
- Experience with log analysis, network security, digital forensics, and incident response investigations.
- Proficiency developing, automating, and improving analytical detection and response systems.
- Clear communication and an impact-focused approach.
- Creative, holistic thinking about risk reduction in complex environments.

## Nice-to-haves
- Adversarial mindset and understanding of threat actor goals, behaviors, and TTPs.
- Experience with software engineering, data processing, and analysis tools such as Databricks, Jupyter, and Trino.
- Familiarity with big data processing and data science frameworks such as PySpark, Pandas, and scikit-learn.
- Experience with tactical threat intelligence or hunting sophisticated enterprise threat actors.
- Familiarity with network observability, security software, or data engineering solutions such as osquery and Splunk/LogScale.
- Experience with UEBA, SIEM, SOAR, or DLP.

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