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Data Platform Engineer - Security (m/f/d)

4 hours ago 2026/10/04
Other Business Support Services
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Job description

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 1. 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
2. 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
3. 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
4. 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
5. 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
6. 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 Certified Data Engineer Professional
Soft Skills
  • 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
Key Competencies
  • Real-Time Data Engineering
  • Cybersecurity Data Platforms
  • Threat Intelligence Integration
  • Data Lake Architecture
  • Cloud Data Engineering
  • Security Analytics Enablement
Ideal Candidate Profile
  • 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


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