Senior Engineer - Access Entitlements

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

We are seeking an exceptional Senior Engineer – Access Entitlements to design and scale the systems that discover, normalize, and reason about who has access to what across our customers' entire data estate — on-prem file shares, Active Directory, and SaaS platforms like SharePoint, Google Workspace, and Microsoft 365. You will build the connectors, pipelines, and graph models that turn millions of raw permission grants into an accurate, queryable picture of access across billions of files and identities, powering least-privilege analysis, access certification, and risk detection for enterprise customers

What You'll Do

Entitlement Scanning: Build and extend connectors that enumerate identities (users, groups, service accounts, computers) and resource-level permissions (ACLs, role assignments, sharing links) across on-prem and SaaS data sources, handling per-connector quirks like SID resolution, inheritance breakage, and nested group membership

Scale & Concurrency: Design entitlement pipelines that safely parallelize across large tenants — correctly handling shared state, batching, and checkpointing so a scan of hundreds of thousands of principals and files can pause, resume, and recover without data loss or duplication

Data Modeling: Own the mapping from raw connector output to normalized entitlement records, and from those records into our identity graph — designing node/edge structures that represent principals, resources, and access grants (including sharing links and group-inherited access) in a way that supports fast traversal at scale

Multi-Store Architecture: Work across the full data path — Elasticsearch for search-driven access, Databricks/Delta for large-scale analytical joins, and a Neptune-backed graph for relationship queries — making deliberate tradeoffs about what gets synced where, and keeping those stores consistent as data volume grows

Entitlement-Activity Correlation: Build the pipelines that join static entitlements against observed activity logs to answer "who can access this, and who actually does" — the core signal behind over-permission detection and access-risk scoring

Reliability & Correctness: Instrument and test for the failure modes unique to entitlement data — partial scans, malformed ACLs, race conditions in concurrent principal writes, and inconsistent state between graph and source-of-truth stores

What You'll Bring

6+ years of professional software engineering experience, with meaningful time spent on identity/access systems, security data pipelines, or large-scale distributed data processing

Strong Go, Java, or Python skills, with direct experience writing concurrent/parallel data pipelines (goroutines, worker pools, or equivalent) and reasoning about race conditions and shared state

Experience with graph databases or graph query languages (Gremlin, Cypher, or similar) and modeling relationship-heavy data

Familiarity with Elasticsearch/OpenSearch and at least one large-scale analytical store (Databricks, Snowflake, BigQuery, Redshift)

Understanding of identity and access concepts — RBAC, ACLs, group membership

Bonus Skills

Experience with Microsoft Graph API, SharePoint REST APIs, or ActiveDirectory/LDAP-based identity systems

Familiarity with AWS Neptune, TinkerPop/Gremlin, or other graph-native databases