Sr. 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.

Data Architecture & Platform Modernization

• 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.

Reliability, Backup & Disaster Recovery

• 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, replication lag, connection saturation, and storage and IOPS headroom — and define SLIs for the data tier.

• Participate in on-call rotations and act as an incident responder for data-tier events, contributing to root-cause analysis and tracking corrective actions to completion.

Security, Privacy & Compliance

• Implement encryption at rest and in transit, key management, and least-privilege database access; replace shared and long-lived credentials with managed identity and short-lived tokens.

• Protect regulated and personally identifiable data — including vehicle, registered-owner, and payment data — through access controls, masking in non-production environments, and defensible retention and purge processes.

Cross-Functional Collaboration

• Partner with Software Engineering so that new services adopt approved data-access patterns, migration tooling, and performance review from day one rather than retrofitting them later.

• Review application data access during code review, and coach engineers on query construction, indexing implications, and transaction scope.

• Document schema ownership, data dictionaries, runbooks, and recovery procedures so that the platform does not depend on any single person’s knowledge.

• Respond to system issues, participate in high-priority incident calls, and support emergency activities outside of standard hours as needed.

Required Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent professional experience.

• 6+ years of experience in database engineering, data platform engineering, or production database administration, including 3+ years working with PostgreSQL at production scale.

• Deep, demonstrable PostgreSQL expertise: execution plan analysis, index and partitioning strategy, autovacuum and bloat management, connection pooling, and lock and deadlock diagnosis.

• Production experience with managed cloud databases (Amazon Aurora PostgreSQL or RDS preferred), including backup and point-in-time recovery, read replicas, and failover testing.

• Hands-on experience with schema migration tooling integrated into CI/CD (Flyway, Liquibase, Alembic, Sqitch, or comparable) and with zero-downtime schema change patterns.

• Strong command of transaction semantics — isolation levels, locking, and concurrency correctness — and the ability to reason about race conditions in application code, not only in the database.

• Advanced SQL, plus proficiency in at least one of: Python, TypeScript/JavaScript, Go, or Bash for tooling and automation.

• Working experience provisioning and changing database infrastructure as code (CloudFormation, Terraform, or comparable).

• Experience with database observability and diagnostic tooling (Performance Insights, pg_stat_statements, CloudWatch, Datadog, or comparable APM).

• Clear, concise written and verbal communication, including the ability to explain data-tier trade-offs to engineers and to non-technical stakeholders.

Preferred Qualifications

• Experience in mobility, transportation, tolling, parking, payments, or other regulated, high-volume transaction-processing environments.

• Experience with GraphQL data-access layers (Hasura, PostGraphile, or similar), and with migrating applications off a generated-API layer onto typed service interfaces.

• Multi-tenant data architecture at scale, including per-tenant account or database isolation and the operational overhead it carries.

• Event streaming and change data capture (Apache Kafka / Amazon MSK, Debezium, transactional outbox patterns) and the consistency guarantees involved.

• Large-scale data migration from legacy platforms, with formal reconciliation and cutover planning.

• Exposure to compliance regimes such as SOX, SOC 2, PCI-DSS, or ISO 27001.

• Analytical and data warehouse platforms (Redshift, Snowflake, dbt) and transactional-to-analytical replication.

• Working familiarity with Oracle or SQL Server for legacy interoperability.

• Relevant certifications: AWS Certified Database — Specialty, AWS Solutions Architect, or a PostgreSQL certification.

What Success Looks Like in the First 9 Months

• Within 90 days: ramped up on the core schema, migration pipeline, and environment topology; owning the migration review process and holding a prioritized baseline of the platform’s highest-cost queries.

• Within 6 months: delivered measurable latency reduction on owned workloads; validated backup and recovery against stated objectives through an actual restore exercise; actively participating in the on-call rotation.

• Within 9 months: recognized as the owner of platform data architecture; retired at least one significant constraint — a legacy data-access dependency, a licensing exposure, or a recurring class of performance failure; mentoring engineers and setting standards the team follows.