Veeamsoftware

Sr. Director, Graph Databases

San Jose, CA, USA · Director

Sponsorship not specifiedDetected 13 days ago
PythonDistributed SystemsBigQueryAWSAzureCloud PlatformsSparkCybersecurityLeadership

About the role

  • Together, they help customers understand where sensitive data lives, who can access it, how it moves, and whether AI models trained on it can be trusted.

Responsibilities

  • Own the strategy for hyperscale lake and lakehouse integrations, including connectors and scanning engines that ingest metadata and lineage from Delta Lake, Iceberg, Parquet/Avro, and platforms like Azure Data Lake, AWS S3/Glue, and BigQuery without disrupting production
  • Drive performance and reliability, including standards for indexing, partitioning, and query planning, and tuning traversals and queries (Gremlin, Cypher/openCypher, SPARQL)
  • Build and scale an AI-first engineering approach where teams use tools like Claude Code, Cursor, and Copilot responsibly, with guardrails for security, maintainability, and code quality
  • Invest in reusable engineering building blocks (including "Claude skills" and agent workflows) that make teams faster and more consistent
  • Hire, coach, and develop leaders, including engineering managers and senior/staff engineers, with clear expectations and growth paths
  • Proven ability to lead graph modeling for complex domains, including lineage and permissions at enterprise scale
  • Deep knowledge of Gremlin, Cypher/openCypher, and/or SPARQL, including performance tuning and query design best practices
  • Strong backend background in Go and/or Python, with the ability to review designs, guide decisions, and unblock teams

Requirements

  • Strong production experience with Amazon Neptune and/or Neo4j, including scaling, operations, and trade-offs (property graph vs.
  • Experience with data lakes/lakehouses (Delta Lake, Iceberg, Parquet) across major cloud platforms (Azure Data Lake, AWS S3/Glue, BigQuery)
  • Strong production experience with Amazon Neptune and/or Neo4j, including scaling, operations, and trade-offs (property graph vs. RDF)

Benefits

  • Set the technical vision and end-to-end architecture for the Knowledge Graph, including the data model, storage engine, and query layer at very large scale
  • Own delivery outcomes: roadmap execution, operational readiness, incident learning, and cross-team alignment

Company info

  • 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.
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This listing is sourced directly from Veeamsoftware's careers page and normalized into a canonical job model.