SecOps Data & Analytics Engineer
Core
Build and maintain data pipelines to collect, route, transform, and deliver security and observability data from diverse sources to downstream platforms.
Role type
Mid-level Security Data & Analytics Engineer (Data Engineering)
Builds
Data ingestion pipelines, transformation workflows, and data quality controls for security operations.
Domain
Cybersecurity / Security Operations / Data Engineering
Deliverable
production ML models | product features | dashboards & analysis | infrastructure
Required skills
Data pipeline development, data ingestion, data transformation, data quality validation, structured/unstructured data handling, API integration, basic scripting (Python/PowerShell/JS), SQL
Preferred skills
Data pipeline certification (Cribl/Onum/Databahn), Observability certification (Datadog/Dynatrace/Splunk), Cloud certification (AWS/Azure/GCP), data masking/retention strategies
Technologies
Agents, APIs, webhooks, syslog, object storage, message queues, JSON, XML, CSV, CEF, Python, PowerShell, JavaScript, SQL
Responsibilities
Configure and support data ingestion from applications, infrastructure, cloud services, and security tools. Develop and maintain pipelines that collect, route, filter, enrich, transform, and deliver data. Implement parsing, field extraction, schema mapping, and normalization for structured and unstructured data. Validate data completeness, consistency, accuracy, and timeliness while troubleshooting delivery issues. Contribute to reusable pipeline patterns, parsers, and implementation standards. Participate in data architecture assessments and document data flows and dependencies. Communicate data-quality issues and technical risks to stakeholders.
Seniority
Mid-level, hands-on IC