Lead Forward Deployed Engineer

Qualys; Maharashtra; On-site; INR 2,800,000 - 5,000,000; Full time

Job summary

Qualys leads enterprise onboarding to integrate cybersecurity data into the Enterprise TruRisk Management platform. You will own end-to-end deployments, design scalable ingestion pipelines, and build data models that unify disparate security feeds into a coherent risk view.

The role requires strong Python/Go skills, API experience, and excellent client-facing communication to translate customer needs into engineering requirements.

Qualifications

• 8–10 years in data engineering, platform engineering, or customer-facing technical roles.
• Strong Python/Go and API experience.
• Experience building scalable ingestion pipelines and data models.
• Excellent communication with clients and internal teams.

Responsibilities

• Lead end-to-end enterprise onboarding from strategy to production rollout for ETM platform.
• Design REST APIs, webhooks, and scalable ingestion pipelines to integrate data sources.
• Develop data models, transformations, and correlation logic; ensure data quality.
• Build dashboards, reports, and support executive reporting.
• Bridge customer needs with product engineering and provide feedback.

Skills

Python

Go

REST APIs

Webhooks

Asynchronous systems

ETL/ELT pipelines

Data modeling

Relational databases

NoSQL databases

Graph databases

Data normalization

Cybersecurity domain knowledge

AI/automation

Communication

Client-facing

Education

Bachelor’s or Master’s in Computer Science, Engineering, or equivalent

Tools

REST API design

Webhooks integration

ETL/ELT tools

Jira/ServiceNow

Job description

Come work at a place where innovation and teamwork come together to support the most exciting missions in the world!

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.