Description

You will design and implement secure, scalable data architectures for cybersecurity applications, supporting real-time analytics and ML-driven insights.

This role is on-site.

Responsibilities

• Design and implement data lakes, warehouses, and lakehouse solutions for secure, high-availability data structures.
• Integrate data science workflows and deploy ML models for batch and real-time processing.
• Build CI/CD pipelines to automate testing, security scans, and deployment for data workflows.
• Implement automated data quality checks, lineage, and governance using Databricks DQM or similar tools.
• Develop analytics and visualizations in Power BI or Tableau to report on threat patterns and vulnerability trends.

Required Skills

• 8+ years of experience in data engineering.
• Expertise in Python, PySpark, and SQL.
• Extensive hands-on experience with Databricks and big data frameworks.
• Advanced proficiency in AWS (EC2, S3, Lambda, ELB).
• Experience with container orchestration using Docker and Kubernetes.
• Proven experience with secure DevOps practices (SCA, SAST, DAST/WAS within SDLX).
• Experience managing large-scale data environments optimized for performance and compliance.
• Experience working in Agile/Scrum environments.

Preferred Skills

• Experience deploying ML models within a cybersecurity context.

Key Skills

Education

Bachelor's degree in Computer Science