Data Engineer - Product Security

Data Engineer - Product Security at Red Hat

At Red Hat, we connect an innovative community of customers, partners, and contributors to deliver an open source stack of trusted, high-performing solutions. But innovation cannot exist without security. The Red Hat Product Security team is the guardian of that trust, ensuring that our portfolio—from Linux to the hybrid cloud—remains secure by design and compliant by default.

We are looking for a Data Engineer - Product Security to help us solve a critical problem: visibility. Our security data comes from dozens of different products, upstream communities, and internal tools. It is messy, high-volume, and constantly changing.

In this role, you will not just move data from point A to point B. You will be the architect of our "single pane of glass," building the pipelines and views that allow our leadership to assess risk, prioritize remediation, and prove compliance to our customers. You will have the opportunity to leverage Artificial Intelligence (AI) to automate the classification and analysis of this vast information landscape, directly influencing the security strategy of a global tech leader.

What You Will Do

• Unify Disparate Data: Design and build robust data pipelines (ETL/ELT) to ingest, clean, and normalize security data from a wide variety of sources (e.g., vulnerability scanners, build systems, issue trackers, and customer feedback loops).
• Enable AI-Driven Insights: Integrate AI and Machine Learning models into our data workflows to identify patterns, predict potential risks, and automate the classification of security signals.
• Visualize Security Posture: Collaborate with security architects and leadership to generate data views and dashboards that accurately reflect the security health of Red Hat products.
• Ensure Data Integrity: Implement automated validation and quality checks. In Product Security, bad data leads to bad risk decisions; your work will ensure we trust the numbers.
• Collaborate Across Teams: Work remotely with a distributed, global team of security engineers, analysts, and developers. You will translate their complex technical requirements into scalable data solutions.
• Innovate: continuously evaluate new tools and open source technologies to improve the efficiency and speed of our data processing.

What You Will Bring

We are less interested in a checklist of specific tools and more interested in your ability to solve complex data problems. If you have the aptitude and the mindset, we can help you learn the specific stack.

• Relevant Experience: Typically, 2+ years of experience in data engineering, software development, or a related field. Note: We welcome applicants with less experience who can demonstrate exceptional aptitude, personal projects, or a strong portfolio of relevant work.
• Data Wrangling Proficiency: Demonstrated ability to manage large datasets. You should be comfortable writing complex SQL and using programming languages (like Python) to manipulate data.
• The AI Advantage: Experience with, or a strong passion for, Artificial Intelligence and Machine Learning. If you have used LLMs to summarize data, or built models to detect anomalies, we want to hear about it. This is a significant plus for this role.
• Problem-Solving Mindset: You are comfortable dealing with ambiguity. You can look at a messy dataset and see the structure hidden within it.
• Communication: Ability to explain technical data concepts to non-technical stakeholders. You can tell the story behind the data.
• Open Source Spirit: A willingness to work in an open, collaborative environment. Familiarity with Linux or open source development practices is beneficial.

Key skills/competency

• Data Engineering
• ETL/ELT Pipeline Development
• Data Wrangling
• SQL
• Python Programming
• Artificial Intelligence (AI)
• Machine Learning (ML)
• Data Visualization
• Security Data Analysis
• Open Source Practices