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.

Key Responsibilities

• Real-Time Security Data Pipelines
• 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
• Threat Intelligence Correlation Engine
• 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
• Cyber Data Lake Architecture
• 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

• Data Engineering & Platform Optimization
• 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
• Security Analytics Enablement
• 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
• Compliance, Audit & Governance
• 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

Qualifications & Experience Education

• Bachelor’s or Master’s degree in:

• Data Engineering
• Computer Science
• Information Systems or related field

Experience

• 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

Technical Skills

• 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

Certifications (Mandatory / Preferred)

• Microsoft Certified: Azure Data Engineer Associate
• Databricks