Description

Job Description:

  • This candidate is responsible for designing and developing in-house Security Information and Event Management (SIEM), Security Orchestration, Automation, and Response (SOAR), and investigative tools, with a primary focus on building robust, scalable, and automated security solutions.
  • In this role, you will be responsible for the end-to-end design, development, testing, deployment, and maintenance of key components within our large-scale data infrastructure.
  • This infrastructure is essential for advancing automation, enabling data-driven insights, and enhancing enterprise-wide security measures.
  • 4-7 years of years’ experience with Data Engineering and AI/ML is mandatory

Responsibilities:

  • Develop and deploy scalable, production-ready software to drive automation and enable data-driven decision-making within the Enterprise Cybersecurity team, prioritizing resilience, performance, and security.
  • Provide engineering support for the Enterprise Cybersecurity Operations team, with a focus on creating automated solutions that reduce manual intervention and operational overhead.
  • Design and build event-driven, scalable systems to deliver timely alerts and automations, enhancing responsiveness and support for both the Cybersecurity team and external stakeholders.
  • Integrate new data sources into our data lake to enhance visibility and extend security coverage across the environment, focusing on building reusable, automated data ingestion processes.
  • Provide development and migration support for the integration of new tools and technologies, ensuring seamless onboarding within the Enterprise Cybersecurity environment.

Qualifications:

  • Extensive programming experience in object-oriented languages (e.g., Python, Go, Java) and SQL, with a proven track record in designing maintainable, scalable, and efficient solutions.
  • Robust expertise in the following areas: distributed data processing, data engineering for high-volume data services, or developing scalable data streaming platforms for real-time analytics.
  • Advanced proficiency in cloud and data infrastructure technologies (e.g., AWS, Databricks, Terraform, Apache Spark, Docker) with deep knowledge of development best practices, CI/CD pipelines, and cloud-native deployment.
  • Comprehensive knowledge of RESTful APIs and data integration techniques to enable efficient, secure, and scalable data flow and communication between security systems and user-facing platforms.
  • Strong familiarity with infrastructure-as-code tools such as Terraform or Ansible to automate and standardize security configurations across diverse environments.
  • Hands-on experience with CI/CD pipelines, version control systems (e.g., Git), and modern software development practices to ensure high standards of consistency, quality, and automation in deploying and updating security tools

 

Key Skills
Education

Any Graduate

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