Database Engineer

Position Overview

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 DevOps 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.

Essential Responsibilities

Schema Design & Change Management

• 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.

Performance Engineering & Query Optimization

• 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.