Senior Manager, Data Security

Autodesk•Boston, MA

36d•$152,000 - $272,250•Remote

About The Position

Autodesk's Information Security Engineering organization is looking for a Senior Manager, Data Security Engineering to lead the engineering strategy and execution for data protection across Autodesk's enterprise environment. This leader will own the data security engineering pillar, with accountability for data classification and discovery, data loss prevention (DLP), cloud data security, and SaaS security posture. Reporting to the Senior Director, Information Security Engineering, this role will build and lead a high-performing engineering team that designs, deploys, and operates scalable data security controls across Autodesk's cloud, SaaS, and endpoint environments. This role requires both strong engineering depth and strong security judgment. The Senior Manager will partner closely with peer leaders across IAM, Network, SaaS, and Endpoint Security Engineering to ensure data-centric security controls are integrated across Autodesk's full technology stack. This leader should bring hands-on experience with Data Security Posture Management (DSPM) and SaaS Security Posture Management (SSPM) platforms, and the ability to translate data risk into engineering outcomes at enterprise scale. This is a forward-looking role: the expectation is not just familiarity with AI-assisted engineering tools, but genuine proficiency. The right candidate actively uses and evaluates the latest AI capabilities to accelerate detection, automate response, and raise the quality bar for their team.

Requirements

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
Strong hands-on experience with DSPM platforms for sensitive data discovery, classification, and risk quantification across cloud environments
Strong 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 SOC 2, 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
Demonstrated proficiency with current AI-assisted engineering and security tools (e.g., coding assistants, AI-driven detection, automated triage), with evidence of using them to meaningfully improve team output and security outcomes
Strong cross-functional leadership and the ability to influence Legal, Privacy, Compliance, Engineering, and People stakeholders

Nice To Haves

Experience with FedRAMP or other regulated environment data security requirements
Experience building data security paved roads and reusable engineering patterns for internal developer and platform teams
Experience with AI-era data risks, including training data exposure, LLM output leakage, prompt injection risk, and vector database security
Experience with data access governance, data lineage, and entitlement-based data risk reduction
Relevant certifications such as CISSP, CISM, or CCSP

Responsibilities

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, SOC 2, FedRAMP) into durable, scalable engineering controls and ensure data security requirements are embedded across the employee and product lifecycle
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, with a high bar for genuine proficiency, not just awareness