Job Opportunities API

Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands. About the Role Veeam is looking for a  Senior Data Security & Privacy Engineer  to own  privacy-by-design  and  data protection engineering  for the  Veeam Data Cloud (VDC) data plane  on  Microsoft Azure   and  AWS .  You will be the dedicated security and privacy engineering partner for VDC, responsible for how customer data is  classified, ingested, encrypted, stored, processed, accessed,  monitored , retained, and  deleted  across VDC workloads.     This is a  product  security  and enablement  role: you will build  shared security/privacy services ,  guardrails , and  paved roads  that make secure, compliant defaults easy for product teams to adopt. You will ship code via  pull requests , provide  reference implementations  and  self-service tooling , and measure adoption to drive consistent protections across the data plane.     What You’ll Do Build and maintain  shared platform capabilities that enable product teams to securely access Veeam Data Cloud and services (humans, services, agents) with secure-by-default patterns. Set standard patterns for  authentication, authorization, and least-privilege access  in a  multi-tenant SaaS  environment, with explicit focus on  customer data access (humans, services, automation, break-glass) . Engineer and operationalize  privacy-by-design controls: data minimization, purpose limitation, and safe-by-default handling of personal/sensitive data (incl. data discovery and classification). Build and maintain  data lifecycle mechanisms (retention policies, legal hold support where applicable, secure deletion, export/erasure workflows) that scale across tenants and regions. Own the  encryption and key management strategy for customer data (in transit and at rest), including key rotation, access policies, and integrations with platform KMS (e.g., Azure Key Vault / managed HSM where used). Define and build a shared  security + privacy control plane  with  internal APIs/SDKs  and  self-service workflows (tenant isolation, policy-as-code, consistent enforcement, abuse/rate limiting, and guardrails that reduce the chance of data exposure). Define  secure logging, audit trails, and telemetry libraries  (what we log, how we  avoid/ redact sensitive data , how logs support detection, incident response, and privacy investigations) . Ship production-quality code (services, SDKs, templates, lint rules, CI/CD checks, infrastructure-as-code guardrails) that creates  paved roads and makes the secure path the default path for product teams. Create  reference architectures , reusable patterns, and developer documentation; run enablement (onboarding, office hours) and define  adoption metrics to drive consistent rollout across teams.   Build scalable  data-flow mapping  and  threat modeling mechanisms (templates, tooling, review checklists) for features that touc