Senior Manager, Data Security

Senior Manager, Data Security Engineering

Autodesk’s Information Security Engineering organization is seeking a Senior Manager to lead the engineering strategy and execution for data protection across the Autodesk enterprise environment. This role owns the data security engineering pillar, with accountability for data classification and discovery, data loss prevention (DLP), cloud data security, and SaaS security posture. The manager reports to the Senior Director, Information Security Engineering, and is responsible for building and leading a high‑performing engineering team that designs, deploys, and operates scalable data security controls across Autodesk’s cloud, SaaS, and endpoint environments.

The role is remote‑friendly within North America. Optional in‑office or hybrid work can be based in San Francisco, CA;
Portland, OR;
Boston, MA;
Denver, CO; or Toronto, ON. Travel requirements are approximately 20%.

• Define the engineering strategy, architecture, and roadmap for Autodesk’s data security capabilities, spanning data classification and discovery, DLP, cloud data protection, and SaaS security posture.
• Lead engineering teams responsible for DSPM, SSPM, DLP platforms, data classification services, and data security integrations.
• Own the design and operation of data discovery and classification pipelines across structured and unstructured data in cloud, SaaS, and endpoint environments.
• Drive engineering for DLP policy enforcement across endpoints, network egress, email, cloud storage, and generative AI surfaces.
• Build and maintain cloud data security controls across AWS, Azure, and GCP, including storage security, data plane visibility, and misconfiguration remediation.
• Establish and mature SaaS security posture management capabilities, including data exposure discovery, third‑party application risk, and configuration enforcement.
• Ensure data security engineering aligns to data minimization, least privilege access, encryption in transit and at rest, and auditability requirements.
• Partner with Legal, Privacy, Compliance, Engineering, and People teams to translate regulatory requirements (GDPR, CCPA, SOC2, FedRAMP) into durable, scalable engineering controls.
• Drive adoption of automated classification, sensitivity tagging, and policy enforcement to reduce manual data handling risk at scale.
• Partner with IAM Engineering on data access governance, entitlement visibility, and access‑based data risk reduction.
• Lead and grow a high‑performing data security engineering organization with strong technical ownership, delivery standards, and production readiness.
• Drive active adoption of the latest AI‑assisted engineering and security tools across the team, maintaining a high bar for genuine proficiency.

• 8+ years of experience in data security, security engineering, or related enterprise security domains.
• 3+ years leading engineering teams responsible for data security platforms, DLP, DSPM, SSPM, or cloud data protection at enterprise scale.
• Hands‑on experience with DSPM platforms for sensitive data discovery, classification, and risk quantification across cloud environments.
• Hands‑on experience with SSPM platforms for SaaS configuration posture, data exposure, and third‑party application risk management.
• Deep knowledge of data classification frameworks, sensitive data discovery, and automated tagging and labeling approaches.
• Experience designing and operating DLP controls across endpoints, network, cloud storage, email, and SaaS applications.
• Experience securing data in cloud environments across AWS, Azure, and GCP, including storage security, data access governance, and visibility tooling.
• Strong understanding of data‑centric regulatory requirements including GDPR, CCPA, and SOC2, and how to translate them into engineering controls.
• Experience integrating data security controls with identity, endpoint, and network security domains.
• Strong engineering fundamentals across APIs, automation, observability, and secure platform delivery.
• Proficiency with current AI‑assisted engineering tools, with evidence of meaningful improvements to team output and security outcomes.
• Strong…