Database Reliability Engineer

About the Role
As a Database Reliability Engineer, you will play a pivotal role in ensuring that our data layer remains efficient and reliable. You will be responsible for database performance, caching reliability, and business continuity/disaster recovery (BC/DR) of the data tier that supports all services. Collaborating with the Platform Engineering squad, you will execute scaling and optimization initiatives, ensuring our databases remain fast, durable, and cost-effective as trading data and traffic grow.

How You'll Make an Impact

Data Performance & Scalability

• Execute database optimization and scaling initiatives, including implementing partitioning strategies, sharding schemes, and replication configurations.
• Independently diagnose and fix slow queries across the platform.
• Own performance diagnostics on high-volume tables, including EXPLAIN plan analysis, index tuning, buffer cache hit-ratio investigation, lock contention, and replication lag on tables with over 100M rows.
• Build and maintain data archiving pipelines to move historical records (trade logs, transaction data, audit trails) from production tables to cold storage (S3/Parquet/Athena/Glacier) while preserving query access for compliance and reporting.
• Implement and maintain data lifecycle automation such as TTL policies, scheduled archival jobs, partition rotation, and retention enforcement.
• Conduct regular performance profiling across the data tier to identify bottlenecks in MySQL/PostgreSQL and the caching layer, followed by implementing measurable fixes.
• Support load testing and capacity planning for the data layer — analyze growth trends, identify breaking points, and implement fixes before traffic growth causes production issues.

Data Reliability & Infrastructure

• Implement and maintain data-tier BC/DR infrastructure, including multi-AZ deployments, read replicas, Aurora Global Database/cross-region replication, backup schedules, and failover triggers targeting RTO/RPO under 5 minutes; participate in regular DR drills.
• Implement and maintain caching strategies (Redis, ElastiCache), covering cache invalidation logic, read-through/write-behind patterns, TTL hygiene, and cache hit-rate monitoring.
• Define and track reliability metrics (SLIs/SLOs) for the data layer, focusing on query latency, availability, and replication health, and drive improvements against them.
• Implement monitoring, alerting, and observability for the data tier, including dashboards, slow-query alerting, and replication/cache health monitoring to minimize Mean Time To Detect (MTTD) on data incidents.
• Maintain and improve database-level automation, including stored procedures, dynamic partitioning scripts, and scheduled maintenance jobs.

Cross-Team Support

• Collaborate with application and product squads to design schemas, indexes, and access patterns that scale.
• Remediate data-related security findings from the Cyber Security Squad by implementing fixes and verifying through retesting.
• Write and maintain infrastructure-as-code for data resources using Terraform or an equivalent for reproducible, version-controlled provisioning.
• Document runbooks, archiving procedures, and operational guidance so any engineer can respond to data-tier incidents with clear guidance.

What You Bring

• 4–6 years of professional engineering experience, with at least 2 years in database-focused infrastructure work at moderate-to-high scale.
• Strong expertise in MySQL and PostgreSQL, including EXPLAIN plan analysis, index design, partitioning, sharding, and replication setup — with hands-on experience on tables with over 100M rows.
• Capability to build data archiving pipelines to cold storage (S3/Parquet/Athena/Glacier) while ensuring records are queryable for compliance and reporting.
• Proficiency with AWS managed database services (RDS and Aurora), comprising provisioning, read replicas, parameter group tuning, and monitoring; experience with Aurora Global Database is a plus.
• Familiarity with Redis and ElastiCache, covering cache invalidation patterns, TTL hygiene, hit-rate monitoring, and incident diagnosis.
• Skills in automating archival, maintenance, and diagnostic work using Python and/or Bash.
• Understanding of monitoring and observability tooling (such as Prometheus, Grafana, Datadog, etc.) for slow-query alerting, dashboards, and data-tier incident analysis.
• Knowledge of multi-AZ and cross-region DR architectures, backup strategies, and failover triggers targeting RTO/RPO under 5 minutes.
• Comfort with writing Terraform or CloudFormation for provisioning data resources in a version-controlled, reproducible manner.
• Ability to write and debug stored procedures and dynamic partitioning logic for database-level automation.

X-Factor: AI-Native Engineering

• You actively use modern AI agentic workflows daily, beyond just Copilot autocomplete.
• Proficiency with tools like Claude Code, Cursor, Windsurf, or equivalents.
• Comfort with project-level AI configuration (CLAUDE.md, rules files), agentic task delegation, and AI-driven code review.
• A mindset aimed at achieving 5–10x productivity through AI-augmented development, with demonstrable evidence of this.

Your Journey After Applying

• Stage 1 — TA Interview
• Stage 2 — Screening Questionnaire
• Stage 3 — Hiring Manager Interview
• Stage 4 — Head of IT Interview

Why Join

• Work on substantial data challenges at real scale — handling 100M+ row tables, 1TB+ databases, and high-frequency trading transaction volumes.
• Join a team that treats database performance and data-tier reliability as primary engineering challenges, rather than peripheral DBA tasks.
• Enjoy a flat organizational structure where your work directly influences the platform's data infrastructure without bureaucratic hurdles.
• Become part of a genuinely global engineering team with offices in various locations.
• Receive competitive compensation benchmarked to your market, with growth opportunities as the team scales.

Experience level: Senior