Consultant, Cybersecurity (Data Engineer)

What you'll do

• Design and operate the security data engineering foundation for telemetry ingestion, normalization, and enrichment.
• Build and maintain production-grade data pipelines and lakehouse data products using Databricks and Spark.
• Develop trustworthy data models that balance performance, cost, lineage, and analytical usability for security investigations.
• Implement data quality monitoring, freshness checks, and reconciliation controls for critical security data flows.
• Optimize cluster performance, storage layouts, and query execution for scale and cost efficiency.
• Define ingestion and curation patterns for diverse security and platform telemetry sources.
• Troubleshoot pipeline defects, telemetry gaps, and downstream data issues during production incident responses.
• Support secure access patterns, governance controls, and auditability requirements for sensitive security data.

What we're looking for

• Typically requires six years of experience in technology, with four years specifically in cyber security.
• Strong data engineering skills with advanced Databricks and Spark experience and proficiency in Python and SQL.
• Experience building and operating batch and streaming data pipelines for high-volume telemetry, logs, and security datasets.
• Strong knowledge of telemetry normalization (OCSF), enrichment, schema design, and data quality controls.
• Experience designing and maintaining lakehouse or data lake architectures for analytics, detections, and investigations.
• Familiarity with detection engineering requirements and integrating enterprise data sources, APIs, and cloud storage.
• Undergraduate studies in cyber security, management information systems, engineering, math, computer science, or data analytics (preferred).
• Preferred certifications include CISSP, CCNA, CEH, GCIH, EnCE, GSTRT, GSE, CCSP, AWS Certified Cloud Practitioner, or AZ500.