Leads PostgreSQL database infrastructure for a global legal AI platform, owning migration governance, multi-region scaling, reliability, performance tuning, and self-service tooling. Requires 10+ years experience with expert PostgreSQL knowledge and staff-level impact.
191k – 286k
HybridDevOps / SRE
About the role
What You'll Do
Migration Governance – Own the migration governance framework end-to-end—design the review workflow, CI gate checks, automated rollback procedures, and fleet-wide deployment sequencing that makes safe migrations the default across the org
Architecture & Scaling – Drive the technical strategy for Harvey’s global database fleet—multi-region replication design, capacity planning, sharding and partitioning approaches, and fleet-wide observability as we scale into new markets
Reliability & Performance – Own database reliability and performance at the fleet level—monitoring replication health, optimizing query performance, tuning vacuum and connection management, and building the alerting that gives us confidence across all production environments
Platform & Tooling – Build self-service tooling and developer guardrails—migration dry-runs, schema diff previews, automated health checks, performance regression detection—so engineering teams can move fast without bottlenecking on a single DBA
Incident Leadership – Lead database incident response and drive systemic improvements—triage production issues, run post-incident reviews, and turn lessons learned into durable process and tooling fixes
Even Better If You Can:
Security & Compliance – Partner with Security and Compliance to design and enforce data-layer controls for SOC 2, GDPR, and data residency requirements—access controls, audit logging, encryption standards, and data lifecycle policies
Strategic Partnership – Represent database engineering in vendor evaluations, build-vs-buy decisions, and technology strategy discussions with engineering leadership
Team Building – Shape the database engineering function at Harvey—define the operating model, set the hiring bar, mentor engineers on database best practices, and build the culture where teams proactively think about data safety
What You Have
10+ years of hands-on experience in database administration, database reliability engineering, or infrastructure engineering with PostgreSQL as your primary database, with demonstrated staff-level scope—you’ve set standards across teams, not just operated within one
Expert-level PostgreSQL knowledge (required)—WAL mechanics, vacuum tuning, logical and physical replication, partitioning strategies, and the ability to debug production issues others can’t. PostgreSQL is our core database and deep fluency is non-negotiable
Track record of building migration governance systems—not just reviewing migrations, but designing the frameworks, tooling, and organizational processes that make safe migrations the default
Experience architecting database infrastructure for multi-region, high-availability environments—replication topologies, failover automation, and data consistency trade-offs at fleet scale
Deep fluency with database observability—you’ve built monitoring strategies using Datadog, pganalyze, or custom instrumentation, and you know which metrics actually predict incidents
Experience leading database major version upgrades (e.g., PostgreSQL 14 → 16) or sharding initiatives in production with zero downtime
Proven ability to influence technical direction across teams without direct authority—you’ve written RFCs, set standards, and changed how an engineering organization thinks about database operations
Proficiency with cloud database services at scale (Azure Database for PostgreSQL, GCP Cloud SQL, or AWS RDS/Aurora) and infrastructure-as-code (Terraform, Pulumi)
Clear communication across audiences—you can present a database architecture decision to the VP of Engineering and explain a migration risk to a junior developer with equal clarity
Bonus
Strong software engineering skills (Python, Go, or similar)—you build production-grade tooling and automation, not one-off scripts
Exposure to vector databases, embedding storage, or adjacent systems (Redis, Elasticsearch, Kafka) relevant to AI/ML workloads in regulated industries
Background building or leading a database engineering function from scratch — defining the team charter, hiring, and operating model
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