Data Platform Engineer - Security; m​/f​/d

Role Purpose

The Data Platform Engineer (Cybersecurity) is responsible for designing, building, and maintaining scalable, real-time data platforms that support security operations, threat intelligence, and cyber forensics
.

This role focuses on developing high-throughput data pipelines
, integrating with SIEM/SOAR systems
, and creating data lake architectures that enable advanced analytics, incident investigations, and audit readiness. The position plays a critical role in ensuring that security data is reliable, structured, and actionable for SOC and risk teams.

• Design and implement real-time data ingestion pipelines for security events
• Integrate pipelines with:
  • SIEM platforms (e.g., Splunk, Sentinel, QRadar)
  • SOAR tools and security monitoring systems
• Ensure high availability, scalability, and low-latency data processing
• Handle large-scale event streaming and log ingestion from diverse sources

• Develop and maintain threat intelligence correlation engines to support SOC operations
• Integrate external and internal threat feeds to:
  • Enrich security events
  • Improve detection accuracy
• Enable real-time correlation and contextualization of threats
• Work closely with SOC teams to refine detection logic and use cases

• Design and manage a centralized cyber data lake for:
  • Security logs
  • Incident data
  • Forensic and audit records
• Ensure the platform supports:
  • Scalable storage and retrieval
  • Data retention and lifecycle policies
  • Compliance with regulatory and audit requirements
• Optimize data structures for:
  • Investigations
  • Reporting and analytics
  • Machine learning use cases

• Build robust ETL/ELT processes for structured and unstructured security data
• Ensure data quality, consistency, and governance across pipelines
• Optimize performance and cost efficiency of cloud-based data platforms
• Implement monitoring, logging, and alerting for data pipeline health

• Enable advanced analytics capabilities for:
  • Threat detection
  • Incident response
  • Behavioral analytics
• Support integration with:
  • BI tools (e.g., Power BI)
  • Machine learning models
• Provide datasets and structures optimized for SOC reporting and dashboards

• Ensure data platforms meet:
  • Internal security policies
  • Regulatory and audit requirements (banking environment)
• Maintain proper data lineage, traceability, and audit trails
• Support audit requests and forensic investigations with reliable data access

• Bachelor’s or Master’s degree in:
  • Data Engineering
  • Computer Science
  • Information Systems or related field

• 8–10 years of experience in:
  • Data engineering / big data platforms
  • Cloud-based data architecture (Azure / AWS)
• Hands‑on experience working with:
  • High-volume, real-time data pipelines
  • Security or operational data systems
• Experience in cybersecurity or SOC environments (highly preferred)
• Exposure to regulated industries (banking/financial services) is an advantage

• Strong expertise in:
  • Azure Data Services (Data Factory, Synapse, Event Hub, etc.)
  • Databricks (mandatory experience preferred)
• Experience with:
  • Streaming technologies (Kafka, Spark Streaming, or equivalent)
  • SIEM/SOAR integrations
• Proficiency in:
  • SQL, Python, or Scala
• Knowledge of:
  • Data lake architectures (Delta Lake, Lakehouse models)
  • Security data schemas and log formats
• Familiarity with:
  • Cloud platforms (Azure, AWS)
  • Data governance and security best practices

• Microsoft Certified:
  Azure Data Engineer Associate
• Databricks Certified Data Engineer Professional

• Strong analytical and problem-solving capabilities
• Ability to manage large-scale data environments
• Effective collaboration with cybersecurity and SOC teams
• Strong documentation and communication skills

• Real-Time Data Engineering
• Cybersecurity Data Platforms
• Threat Intelligence Integration
• Data Lake Architecture
• Cloud Data Engineering
• Security Analytics Enablement

• Experienced data engineer with strong cloud and streaming expertise
• Proven ability to handle high-volume, real-time security data
• Familiar with SOC operations and cybersecurity data use cases
• Capable of designing platforms that support analytics, investigations, and compliance
• Strong balance of engineering depth and operational reliability