Job Description
Cybersecurity Data Platform Engineering
Design and implement
enterprise-scale cybersecurity data platforms for ingesting and analyzing security telemetry and threat intelligence.Build scalable pipelines for
security logs, network telemetry, identity events, and endpoint data.Enable analytics use cases such as
threat detection, anomaly detection, incident response, and security reporting.
Cloud & Data Architecture
Architect and implement
AWS-based data lake and analytics platforms using services such as S3, Glue, Athena, Redshift, and Lambda.Design secure and scalable
Snowflake data platforms for security analytics workloads.Develop
batch and streaming pipelines to process high-volume cybersecurity datasets.
Data Engineering & Pipeline Development
Develop high-performance pipelines using
PySpark, Spark SQL, Python, and AWS Glue.Build orchestration workflows using
Apache Airflow for automated data processing and monitoring.Implement
incremental and event-driven ingestion frameworks using messaging services such as SNS/SQS.
Security, Governance & Compliance
Implement
secure data architectures including encryption, IAM-based access controls, and RBAC.Support regulatory and security compliance through
data governance, lineage, and audit logging.Ensure secure handling of sensitive security telemetry and threat intelligence data.
Platform Performance & Cost Optimization
Optimize
Snowflake performance and cost efficiency through warehouse tuning, clustering, and workload isolation.Implement monitoring, alerting, and automated optimization strategies for cloud data infrastructure.Improve query performance and resource utilization across AWS analytics services.
Collaboration & Leadership
Partner with
security operations (SOC), threat intelligence, and incident response teams to support cybersecurity analytics.Work closely with data scientists to enable
ML-driven threat detection and behavioral analytics.Lead architecture discussions, code reviews, and technical mentoring for data engineering teams.
Required Qualifications
12+ years of experience in
data engineering or data platform developmentStrong expertise in
AWS cloud data services (S3, Glue, Athena, Redshift, IAM)Advanced knowledge of
Snowflake architecture, optimization, and securityProficiency in
Python, PySpark, and SQLExperience with
Apache Airflow orchestration frameworksHands-on experience building
large-scale batch and streaming data pipelinesPreferred Qualifications
Experience working with
security telemetry, SIEM, or cybersecurity analytics platformsKnowledge of
threat detection pipelines and security data modelingExperience integrating with
security tools such as Splunk, Sentinel, or other SIEM platformsFamiliarity with
ML-based anomaly detection or behavioral analyticsExperience with
Infrastructure-as-Code (Terraform) Job Requirements Cybersecurity Data Platform Engineering
Design and implement
enterprise-scale cybersecurity data platforms for ingesting and analyzing security telemetry and threat intelligence.Build scalable pipelines for
security logs, network telemetry, identity events, and endpoint data.Enable analytics use cases such as
threat detection, anomaly detection, incident response, and security reporting.
Cloud & Data Architecture
Architect and implement
AWS-based data lake and analytics platforms using services such as S3, Glue, Athena, Redshift, and Lambda.Design secure and scalable
Snowflake data platforms for security analytics workloads.Develop
batch and streaming pipelines to process high-volume cybersecurity datasets.
Data Engineering & Pipeline Development
Develop high-performance pipelines using
PySpark, Spark SQL, Python, and AWS Glue.Build orchestration workflows using
Apache Airflow for automated data processing and monitoring.Implement
incremental and event-driven ingestion frameworks using messaging services such as SNS/SQS.
Security, Governance & Compliance
Implement
secure data architectures including encryption, IAM-based access controls, and RBAC.Support regulatory and security compliance through
data governance, lineage, and audit logging.Ensure secure handling of sensitive security telemetry and threat intelligence data.
Platform Performance & Cost Optimization
Optimize
Snowflake performance and cost efficiency through warehouse tuning, clustering, and workload isolation.Implement monitoring, alerting, and automated optimization strategies for cloud data infrastructure.Improve query performance and resource utilization across AWS analytics services.
Collaboration & Leadership
Partner with
security operations (SOC), threat intelligence, and incident response teams to support cybersecurity analytics.Work closely with data scientists to enable
ML-driven threat detection and behavioral analytics.Lead architecture discussions, code reviews, and technical mentoring for data engineering teams.
Required Qualifications
12+ years of experience in
data engineering or data platform developmentStrong expertise in
AWS cloud data services (S3, Glue, Athena, Redshift, IAM)Advanced knowledge of
Snowflake architecture, optimization, and securityProficiency in
Python, PySpark, and SQLExperience with
Apache Airflow orchestration frameworksHands-on experience building
large-scale batch and streaming data pipelinesPreferred Qualifications
Experience working with
security telemetry, SIEM, or cybersecurity analytics platformsKnowledge of
threat detection pipelines and security data modelingExperience integrating with
security tools such as Splunk, Sentinel, or other SIEM platformsFamiliarity with
ML-based anomaly detection or behavioral analyticsExperience with
Infrastructure-as-Code (Terraform)