Position: Cyber Data Product/ technical Lead
Location: Juno Beach, FL
"The Cyber Data Product/ Technical Lead owns the strategy, roadmap, and technical delivery of cybersecurity data products that power detection, response, exposure management, compliance, and executive reporting. This role blends product leadership with hands-on technical direction—defining data models and pipelines, integrating
telemetry from security platforms, enforcing data governance and security, and enabling analytics teams with reliable, scalable, and well-documented cyber data capabilities."
Key Responsibilities
Product Leadership & Strategy
"Define the vision, roadmap, and success metrics for cyber data products (SIEM analytics, exposure/CTEM datasets, identity risk models, data security insights)."
• Translate stakeholder needs (SOC, IR, Vulnerability, Cloud, IAM, GRC, Execs) into prioritized backlogs, requirements, and release plans."
• Establish service levels (freshness, availability, quality) and manage product lifecycle, versioning, and change control."
Architecture & Data Modeling
• Design domain models and semantic layers for cyber data (alerts, findings, assets, identities, vulnerabilities, misconfigurations, detections)."
• Define canonical entitles, conformed dimensions (asset, user, application, business service), and reference data (severity, ownership, environment)."
Guide patterns for SCD strategies, event schemas, CDC, and metric definitions/KPls (e.g., MTTR, backlog burn-down, coverage)."
Engineering & Integration
Lead the design of scalable data pipelines (ELT/ETL, APls, streaming) to ingest telemetry from SIEM, EOR/NDR, CSPM/CIEM, ASM, vulnerability scanners,
IAM/PAM, and CMDB/ITSM."
• Oversee performance, reliability, and cost optimization across warehouses/lakehouses; enforce CI/CD and testing standards.
• Drive data quatity(compteteness, deduplication,reconciliation), lineage, and observability(schema drift, freshness, failure alerting). Security, Comptiance & Governance
• Implement access controls (RBAC/ABAC), RLS/CLS, encryption, and privacy-by-design for sensitive data (PII/PHI)."
• Ensure alignment with security frameworks and controls (e.g., NIST CSF, CIS, SOX/PCI/HIPAA/GDPR reporting needs).
• Partner with GRC and Audit on evidence generation, data retention, and defensible documentation. Analytics & Enablement
• De\iver certified, reusable datasets for SOC ana\ytics, exposure/CTEM reporting, and executive dashboards.
• Enable analysts with self-service models, data dictionaries, and query patterns (DAX/SQL).
• Mentor devetopers/analysts; run design reviews, best-practice sessions, and office hours."
"Stakehotder & Vendor Management
• Coordinate across security, IT, data engineering, cloud, and apptication teams; manage dependencies and release planning.
• Oversee vecdor retationships (SIEN/CSPM/ASMNutn/DSPI''ñ), integrations, and ticensin@capacity implications for data flows."
"Required Quaifications
• Experience: 7-1 0+ years across data engineering/architecture or analytics engineering, with 3-5+ years in cybersecurity data domains.
Technical Expertise:"
Data Platforms: Snowflake, Databricks (Delta), BigQuery, Synapse/Fabric (or equivalents)."
Pipelines: dbt, ADF/Glue/Databricks Jobs/Airflow; RESTAPIs; streaming (Kafka/Event Hubs)."
Security Sources: SIEM (Sentinel, Splunk), EOR/NOR, CSPM/CIEM (e.g., Wiz, Prisma), Vulnerability (Tenable/Qualys/Rapid7), ASM, IAM/PAM, CMDB/ITSM (ServiceNow)."
Nodeling/BI: DimensionaPsemantic modeling; Power BI/Tableau; DAX/Power Query(M) a plus."
Languages: Advanced SQL; Python for transformation/automation; Git-based CI/CD."
Product Skills: Backlog management, roadmap definition, stakeholder alignment, measurable outcomes/KPls."
Governance & Security: Data quality practices, lineage/catalogs (Purview/Collibra/Alation), access control and privacy patterns."
Preferred Qualifications
• Experience with CTEN analytics (risk-based prioritization using CVSS, EPSS, KEV, asset criticality)."
• Knowledge of identity context (Entra/AD, SailPoint, CyberArk, Okta) for access risk analytics."
• Familiarity with DSPN/DLP (e.g., Cyera, Securiti, BiglD, Guardium) and data classification."
• Exposure to metric stores/semantic layers, feature stores, or ML-ready pipelines.
• Background in regulated industries and audit-ready documentation.
Core Competencies
Technical Leadership: Guides architecture and delivery; raises engineering standards."
Systems Thinking: Sees end-to-end—from sources and controls to analytics and decisions."
• Data Quality Mindset: Proactive about definitions, lineage, and reconciliation.
• Security-by-Design: Embeds least privilege, encryption, and comptiance from the start.
• Product Orientation: Outcome-driven with clear value hypotheses and success metrics.
• Communication & Enabtement: Transtates comptex designs into clear guidance and reusable patterns.
Tooting(Illustrative)
Data & Pipelines: Snowflake, Databricks/De\ta, BigQuery, Synapse/Fabric; dbt,
ADF/Glue/Airflow; Kafka/Event Hubs.
Security Sources: Microsoh SentineVSplunk; Tenable/Qualys/Rapid7; Wiz/Prisma; ASN platforms; Entra/AD/Okta/SaitPoint;CyberArk; ServiceNow CMDB/ITSM.
BI & Catatog: Power BI (Tabular/DAX), Tableau; Purview/Collibra/A\ation; GitHub/Azure Devops for CI/CD."
Ops & Obsewability: Monitor pipetine health (freshness, faitures, drift), query performance, and cost dashboards."
Thanks,
Never miss an opportunity! Create an alert based on the job you applied for.
