Lead the migration of Vanta’s resource data model from a Mongo-centric solution to a schema-aware Postgres-backed solution and running both generations in parallel without breaking a customer integration
Drive solutions across teams that you do not own but are dependent on the platform built by your team
Design for correctness under eventual consistency with idempotent session handling, conditional writes that survive out-of-order delivery, reconciliation rather than strict cross-service validation, and explicitly backpressure instead of implicit database limits
Design and evolve Vanta's data ingestion and pipeline architecture, ensuring reliable, high-throughput processing of terabyte-scale data streams across distributed systems
Take our Query API from internal use to a production platform with schema versioning, joins and exports, per-tenant isolation, and predictable latency under load
Build data infrastructure where correctness is externally auditable as the evidence Vanta produces has to hold up in front of an auditor
Diagnose the failures that only appear at production data shapes and can include hot partitions, unbounded fan-out, and online rewrites of continuously-written tables
Set architectural direction for streaming infrastructure (Kafka and event queuing), caching layers (Redis), and persistent storage (Postgres, MongoDB) across the Foundations stack
Mentor senior engineers across the team, raising the technical bar through design reviews, architectural guidance, and hands-on contributions to the most complex systems challenges
Champion engineering excellence in reliability, observability, and operational hygiene across the data infrastructure that powers Vanta's core product
Leverage AI tools and systems to accelerate your own work and explore how they can improve the systems you build