Data Engineer – Threat Intelligence

🕒 May 5

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HEROIC Cybersecurity

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2015

🔒 Cybersecurity

☁️ SaaS

🏢 Enterprise

Cybersecurity • SaaS • Enterprise

HEROIC Cybersecurity is an AI-powered identity threat intelligence and dark-web monitoring company that continuously scans breaches, stealer logs, paste sites, and underground marketplaces to detect exposed credentials, API keys, session tokens, and other sensitive data. It provides breach monitoring, threat intelligence, automated remediation workflows, incident response, MSP/MSSP support, APIs and data partnerships, and a SaaS platform (DarkWatch/DarkHive/Cyberlytics) to help security teams and organizations identify, prioritize, and remediate identity-based risks at scale while supporting compliance requirements.

📋 Description

• Architect and operate large-scale, distributed crawling and discovery systems across surface web, deep web, and dark web. • Continuously discover, archive, and download newly released datasets, logs, credentials, and artifacts. • Build automated collectors and archivers for anonymized and decentralized networks. • Develop automated scanning systems to identify unsecured databases and exposed cloud storage. • Build ETL pipelines to clean, normalize, enrich, and index structured and unstructured data. • Automate deployment, scaling, and monitoring using Docker, Kubernetes, and cloud infrastructure. • Continuously optimize performance, reliability, and cost efficiency of crawler clusters.

🎯 Requirements

• Minimum 4 years of hands-on experience in data engineering, intelligence collection, crawling, or distributed data pipelines. • Strong Python expertise and experience with frameworks such as Scrapy, Playwright, Selenium, or custom async systems. • Proven experience operating high-volume, automated data collection systems in production. • Deep understanding of web protocols, HTTP, DOM parsing, and adversarial scraping environments. • Experience with asynchronous, concurrent, and distributed architectures. • Familiarity with SQL and NoSQL databases (PostgreSQL, MongoDB, Elasticsearch, Cassandra). • Strong Linux/Unix, shell scripting, and Git-based workflows. • Experience deploying and operating systems using Docker, Kubernetes, AWS, or GCP. • Excellent analytical, debugging, and problem-solving skills. • Strong written and verbal communication skills.

🏖️ Benefits

• Professional Growth: Amazing upward mobility in a rapidly expanding company. • Innovative Culture: Be part of a team that leverages AI and cutting-edge technologies.