Cybersecurity Data Engineer

Accountabilities: Design scalable data ingestion pipelines: Develop and implement robust architectures for collecting, processing, routing, and transforming security telemetry and other high-volume data sources. Manage security telemetry flows: Build and optimize data flows that support enterprise cybersecurity operations, ensuring data is delivered efficiently and consistently to downstream systems. Configure data routing and ingestion tools: Use platforms such as Cribl, Vector, or comparable technologies to manage telemetry routing, data transformation, and pipeline orchestration. Develop reusable ingestion frameworks: Create standardized patterns, templates, and frameworks that simplify pipeline implementation, promote consistency, and accelerate future deployments. Build modular data architectures: Design maintainable, scalable, and adaptable data flow solutions that support changing data volumes, integration requirements, and security use cases. Leverage open-source technologies: Evaluate and implement open-source and platform-agnostic tools to improve flexibility, reduce operational complexity, and support efficient data processing. Optimize pipeline performance: Identify bottlenecks, troubleshoot data flow issues, and refine ingestion processes to improve reliability, scalability, and operational efficiency. Support enterprise security data operations: Collaborate with relevant technical stakeholders to align data engineering solutions with cybersecurity monitoring needs, infrastructure requirements, and organizational objectives. Requirements Practical experience engineering data flows or pipelines for security telemetry or comparable high-volume data environments. Demonstrated ability to design, implement, and maintain scalable data ingestion pipelines and complex data processing workflows. Experience using Cribl, Vector, or similar data routing, ingestion, and processing platforms. Ability to develop reusable ingestion patterns, frameworks, templates, and standardized pipeline components. Familiarity with open-source data technologies and platform-agnostic tooling for data routing, transformation, and orchestration. Strong understanding of modular data architecture principles, including scalability, maintainability, reusability, and operational consistency. Analytical and troubleshooting skills, with the ability to investigate pipeline issues, evaluate technical trade-offs, and implement effective solutions. Strong organizational skills, attention to detail, and the ability to work independently in a remote, contract-based environment. Effective communication and collaboration skills to coordinate with technical teams and support shared engineering objectives. Location and employment: This is a remote contract opportunity for candidates based in the United States. Applicants should be prepared to provide their current location and work authorization details as part of the application process. Benefits Competitive hourly compensation: Indicative contract rate of $40–$50 per hour , depending on experience, skills, and project requirements. Remote work flexibility: Work remotely from within the United States, offering greater flexibility in your working environment. Contract engagement: An opportunity to contribute specialized engineering expertise to cybersecurity data infrastructure projects. Hands-on technical experience: Work with security telemetry, scalable ingestion architectures, pipeline orchestration, and modern data routing technologies. Exposure to industry tools: Apply and expand your knowledge of Cribl, Vector, and other open-source or platform-agnostic data engineering solutions. Reusable engineering solutions: Develop frameworks and modular architectures that can support broader enterprise security data operations. Professional growth: Strengthen your experience in cybersecurity data engineering, high-volume data processing, and scalable pipeline design.