Issue Resolution: Execute controlled reprocessing and configuration adjustments to fix data quality issues without disrupting operational metrics.
Dashboards, Remediation & Workflows
Analytics & Modeling: Build customized dashboards, trend visualizations, and risk scoring models, including complex "toxic risk combination" scenarios.
Workflow Automation: Integrate ETM with ticketing/remediation tools (Jira, ServiceNow) and configure automated alerts, escalations, and ownership mapping.
Executive Reporting: Develop custom reports/utilities using public APIs for board-level, operational, and regulatory audiences.
Product & Engineering Feedback Loop
Roadmap Influence: Translate field deployment challenges and recurring integration gaps into technical requirements for product and core engineering teams.
Customer Maturity: Guide enterprises from initial risk visibility to automated, remediation-driven action.
Required Qualifications
Education: Bachelor’s or Master’s in Computer Science, Engineering, or equivalent practical experience.
Experience: 8–10 years in data engineering, platform engineering, or customer-facing technical roles.
Technical Stack
Strong programming proficiency in Python, Go, or similar languages.
Deep experience with REST APIs, webhooks, asynchronous systems, and scalable ingestion pipelines (ETL/ELT).
Hands-on knowledge of relational, NoSQL, search, or graph databases.
Domain & Data Expertise
Strong foundation in data modeling, normalization, transformation, and correlation.
Solid understanding of core cybersecurity domains (VM, Cloud Security, IAM, Risk Frameworks).
Hands-on application of AI or automation to optimize data pipelines and onboarding workflows.
Soft Skills: Exceptional client-facing, communication, and technical consultation skills.
Preferred Qualifications
Background in Forward Deployed Engineering, Solutions Engineering, or Technical Professional Services.
Familiarity with large-scale, distributed systems and microservices architectures.
Proven ability to thrive in high-impact, fast-paced, and ambiguous production environments.
