Sr. Database Engineer

We are seeking an experienced Senior Database Engineer to own the design, performance, and operational integrity of the relational data platform behind our mobility products. This is a hands‑on senior individual contributor role accountable for schema architecture, migration safety, query performance, and data durability across a high‑volume, multi‑tenant transaction platform running on Amazon Web Services (AWS).

You will work alongside software engineers, platform and Dev Ops engineers, and architects, partnering closely with Product, QE, and Information Security to support hundreds of microservices that read and write shared operational data stores. Success in this role is measured by query and transaction performance, the safety and cadence of schema change, data durability against recovery objectives, and the retirement of data‑access patterns that constrain platform scalability.

• Own the relational schema for the core operational platform — entity and domain modeling, normalization decisions, constraint and index design, and reference and seed data managed as versioned, reviewable artifacts.

• Author and review database migrations as code, enforcing backward‑compatible, zero‑downtime change patterns (expand/contract, dual‑write, backfill‑then‑cut) so that schema releases decouple from application releases.

• Maintain migration history as the authoritative record of applied state across every environment and tenant, including drift detection and reconciliation where environments have diverged.

• Define and enforce standards for constraints, foreign keys, nullability, and uniqueness so that data integrity is guaranteed by the database rather than by application convention.

• Profile and tune high‑volume OLTP workloads: execution plan analysis, index strategy, partitioning, planner statistics and behavior, connection pooling, and vacuum and autovacuum tuning.

• Diagnose and remediate latency and timeout failures end to end, including cases where the database is the symptom rather than the cause — client‑side timeout misconfiguration, retry storms, N+1 access patterns, and repeated plan regeneration.

• Establish query performance budgets and regression detection so that performance is validated before release rather than discovered in production.

• Review transaction boundaries, isolation levels, and locking strategy to ensure correctness under concurrency — including explicit row‑level locking where read‑then‑write races would otherwise permit duplicate or conflicting processing.

• Lead the consolidation of data access away from generated API layers and ad‑hoc SQL embedded in application code, toward typed, reusable domain services with clear ownership boundaries.

• Reduce third‑party data‑layer dependencies and associated licensing exposure by staging replacements at the infrastructure seam, environment by environment, with no change in application behavior.

• Support migration of client data from legacy platforms, including mapping, transformation, load, and formal reconciliation against source‑of‑record counts and balances.

• Partner with Architecture on the separation of transactional and analytical workloads, reporting replicas, and downstream data warehouse feeds.

• Own backup, point‑in‑time recovery, replication, and failover configuration, and validate it through real restore exercises rather than assumed capability.

• Ensure recovery configuration meets contractual RPO and RTO commitments, and produce the evidence that demonstrates compliance.

• Build database observability — wait events, slow query capture,…