Lead Forward Deployed Engineer

Job description

Come work at a place where innovation and teamwork come together to support the most exciting missions in the world! The Lead Forward Deployed Engineer operates at the intersection of engineering, data, and customer deployment. In this hands-on, customer-facing role, you will lead complex enterprise onboardings to integrate, transform, and operationalize cybersecurity data into Qualys’ Enterprise TruRisk Management (ETM) platform. You will translate fragmented security environments into a unified risk model while bridging the gap between customer needs and core product engineering. Key Responsibilities Customer Onboarding & Data Integration Strategic Execution: Lead end-to-end enterprise onboarding from strategy to production rollout, serving as the system of record for customer assets, findings, and business context. Pipeline & API Design: Build REST API, webhook, and scalable ingestion (e.g., S3-based ETL/ELT) pipelines to integrate diverse data sources (VM, EDR/XDR, Cloud, IAM, CMDBs, GRC). Data Modeling & Correlation: Design custom mapping, transformation, tagging, and asset criticality scoring; implement de-duplication and correlation logic across heterogeneous security feeds. Pipeline Reliability: Ensure continuous full and incremental data ingestion with automated scheduling, monitoring, and error handling. Data Quality & Validation Data Integrity: Establish scalable validation frameworks to audit and maintain asset/findings accuracy for confident risk decision-making. 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.