Data Platform Engineer -Security Analytics & SOC Platforms
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Key skills for this role
About the Role
We are seeking a Cyber Data Engineer to design and maintain real-time data platforms for Security Operations Center, threat intelligence, and cyber forensics.
Key Skills for This Role
Responsibilities
- Design, build, and operate real time security event ingestion pipelines integrating with SIEM/SOAR platforms
- Develop and tune correlation engines that enrich, normalize, and correlate threat intel with live security telemetry
- Design and maintain a centralized cyber data lake on cloud platforms for security logs, alerts, netflow, endpoint telemetry, and forensics artifacts
- Partner with SOC, Threat Intel, and Forensics teams to support analytics and reporting needs
- Ensure data platforms meet SLAs for availability, freshness, and accuracy
- Manage cloud native data infrastructure on AWS, Azure, or GCP, optimizing cost, performance, and scalability
- Automate infrastructure as code and CI/CD for data pipelines
Requirements
- 8+ years in data engineering with 5+ years building security or high volume operational data platforms
- Experience with SIEM/SOAR data integration essential
- Strong skills in Python, SQL, and distributed data processing using Spark, Flink, Kafka, or Kinesis
- Experience with dbt, Airflow, or similar orchestration
- Hands on with AWS, Azure, or GCP data services
- Understanding of SOC workflows, security telemetry, MITRE ATT&CK, and threat intel formats like STIX/TAXII
- Experience with SIEM query languages: SPL, KQL, or AQL
- Proven ability to design data lakes/lakehouses for large scale, business critical data
- Knowledge of data privacy, logging standards, and audit requirements in regulated industries
- Certifications: Microsoft Certified: Azure Data Engineer Associate or Databricks Certified Data Engineer Professional
Full Job Posting
Job Summary
- We are seeking a Cyber Data Engineer to design and maintain real time data platforms that power our Security Operations Center, threat intelligence, and cyber forensics capabilities.
Key Responsibilities
- Real Time Security Data Pipelines: Design, build, and operate real time security event ingestion pipelines integrating with SIEM/SOAR platforms including Splunk, Sentinel, QRadar, or Cortex XSOAR.
- Threat Intelligence Correlation Engines: Develop and tune correlation engines that enrich, normalize, and correlate threat intel with live security telemetry for SOC use cases.
- Cyber Data Lake Architecture: Design and maintain a centralized cyber data lake on cloud platforms for security logs, alerts, netflow, endpoint telemetry, and forensics artifacts.
- Analytics & Forensics Enablement: Partner with SOC, Threat Intel, and Forensics teams to support analytics and reporting needs.
- Data Reliability & Governance: Ensure data platforms meet SLAs for availability, freshness, and accuracy.
- Platform Engineering & Optimization: Manage cloud native data infrastructure on AWS, Azure, or GCP.
Required Qualifications & Skills Experience
- 8+ years in data engineering with 5+ years building security or high volume operational data platforms.
- Strong skills in Python, SQL, and distributed data processing using Spark, Flink, Kafka, or Kinesis.
- Hands on with AWS, Azure, or GCP data services: S3/ADLS/GCS, Glue/Databricks/Synapse, Athena/BigQuery, Redshift/Snowflake.
- Understanding of SOC workflows, security telemetry, MITRE ATT&CK, and threat intel formats like STIX/TAXII.
- Proven ability to design data lakes/lakehouses for large scale, business critical data.
- Knowledge of data privacy, logging standards, and audit requirements in regulated industries, preferably banking/financial services.
- Certifications (Anyone Must): Microsoft Certified: Azure Data Engineer Associate, Databricks Certified Data Engineer Professional.
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