Sezzle is hiring a Senior Database Reliability Engineer

Responsibilities

• Design, build, and maintain shared database platform components used by Sezzle applications, such as database connection packages, database client libraries, migration tooling, safety checks, query standards, and developer-facing abstractions.
• Establish reliable, scalable patterns for how Sezzle services connect to and interact with relational databases across production, staging, and development environments.
• Partner with backend engineering teams to improve database usage in application code, including connection lifecycle, transaction handling, retries, timeouts, pooling, query patterns, and migration workflows.
• Build automation and internal tooling that makes database operations safer, more repeatable, and less dependent on manual intervention.
• Define and enforce engineering standards for database access, schema design, migrations, indexing, query performance, connection management, and operational readiness.
• Architect and improve database infrastructure across AWS RDS/Aurora MySQL, PostgreSQL, RDS Proxy, read replicas, backups, failover, parameter groups, monitoring, and capacity planning.
• Lead database reliability initiatives that reduce operational risk, improve performance, and help Sezzle scale safely.
• Review application designs and database changes early in the development lifecycle to ensure reliability, scalability, maintainability, and security are built in from the start.
• Build guardrails for database migrations, including automated checks, rollback expectations, schema review workflows, migration observability, and production safety controls.
• Improve developer self-service for database provisioning, access, schema management, local development, testing, and observability.
• Investigate production database issues by combining application telemetry, database metrics, logs, query plans, traces, and cloud infrastructure data.
• Identify and fix systemic database problems, not just symptoms — including bad access patterns, unsafe migrations, inefficient queries, connection storms, lock contention, replication lag, and capacity bottlenecks.
• Create and maintain high-signal dashboards, alerts, SLOs, SLIs, runbooks, and operational readiness checks for database-backed services.
• Drive improvements in database backup validation, restore testing, disaster recovery, failover readiness, and business continuity.
• Work with security and compliance teams to improve database access controls, auditability, encryption, secrets management, least privilege, and PCI/SOC 2 aligned controls.
• Mentor engineers on database design, query performance, safe migrations, operational readiness, and production debugging.
• Use automation and AI tooling where appropriate to improve migration review, query analysis, incident investigation, documentation, and developer productivity.

Requirements

• 6+ years of professional software engineering, infrastructure engineering, database engineering, SRE, or platform engineering experience.
• Strong software engineering ability in at least one production programming language such as Go, Python, or TypeScript.
• Proven ability to build production-quality internal tools, libraries, frameworks, services, or platform components used by other engineers.
• Deep hands-on experience with relational databases, especially MySQL and/or PostgreSQL, in high-availability production environments.
• Strong understanding of how application code interacts with databases, including connection pooling, transactions, isolation levels, retries, timeouts, deadlocks, locking, migrations, and query execution.
• Experience designing or improving shared database access patterns, internal database packages, ORM wrappers, migration frameworks, or developer-facing database tooling.
• Hands-on experience with AWS RDS/Aurora, including provisioning, upgrades, replicas, backups, failover, monitoring, parameter tuning, and production troubleshooting.
• Experience with database connection management technologies such as RDS Proxy, PgBouncer, ProxySQL, or application-level pooling.
• Strong ability to analyze database performance using query plans, indexes, slow query logs, wait events, locks, metrics, and application traces.
• Experience designing safe database migration processes for production systems.
• Strong understanding of observability for database-backed applications, including metrics, logs, traces, SLOs, alerting, and incident response.
• Experience with infrastructure-as-code and CI/CD systems such as Terraform, GitLab CI/CD, Kubernetes, Helm, or similar tooling.
• Ability to influence engineering teams through clear design reviews, documentation, technical standards, and practical implementation.
• Ability to operate independently, identify high-impact problems, propose pragmatic solutions, and drive them to completion.
• Demonstrated experience working with Claude or equivalent large language model tools is required; candidates must be comfortable leveraging AI to enhance productivity, research, and communication.
• Bachelor’s degree in Computer Science.

Nice to Have

• Experience building platform capabilities for a microservices environment.
• Experience with Golang application development and database access patterns.
• Experience creating database libraries, SDKs, service templates, migration frameworks, or paved-road developer tooling.
• Experience improving database reliability across many services or teams, not just one application.
• Experience with fintech, payments, banking, e-commerce, or other high-volume transactional systems.
• Experience with compliance-sensitive environments such as PCI DSS, SOC 2, or SOX.
• Experience with database access governance, audit logging, secrets management, encryption, IAM authentication, and least-privilege access models.
• Experience with large-scale operational automation for provisioning, patching, failover testing, backup validation, access management, or schema review.
• Experience with distributed systems patterns such as transactional outbox, event-driven architecture, idempotency, queues, eventual consistency, and data consistency tradeoffs.
• Experience with observability tools such as Prometheus, Grafana, Datadog, CloudWatch, Performance Insights, OpenTelemetry, or New Relic.
• Familiarity with Elasticsearch or other supporting data stores.
• Familiarity with AI developer tooling such as Claude Code, Gemini CLI, Codex, Cursor, and using it to be a more productive engineer.