Staff Database Reliability Engineer

Your Opportunity

Our client builds a high throughput system powering hundreds of billions of daily transactions, each completed within milliseconds, across globally distributed infrastructure designed for reliability and efficiency. They have been quietly bootstrapping and growing in line with revenue for over 2 decades. They maintain independence from external stakeholders, enabling them to chart their course, maintain a long-term perspective and build an enduring, sustainable business that currently employs ~600 team members globally.

Data is central to nearly every part of their platform. High-volume event and transactional data powers customer reporting, billing, marketplace analytics, experimentation, machine-learning workflows, and product experiences. The organization is evolving from centralized, batch-oriented reporting toward a platform-driven architecture combining batch, streaming, and asynchronous processing, with APIs becoming a primary interface to data.

Our client has been stubbornly racking and stacking infrastructure around the world for the duration of their existence, a habit that allows for them to price themselves at the cost of electricity while their competitors are mired in rising cloud infrastructure costs. This long-term, somewhat contrarian, thinking puts them in a position to offer stability and career longevity evidenced by robust benefits that include RRSP matching.

This is an IC role for someone who can move comfortably between deep technical problem solving and broader architectural leadership. You’ll help define how database systems are designed, operated, automated, observed, and evolved across the organization. You’ll work closely with platform engineering, infrastructure, software engineering, operations, and data teams to improve reliability and scalability while championing simplicity in a sophisticated technology landscape.

Key Responsibilities

• Database architecture & reliability: Design and evolve globally distributed database systems for performance, availability, scalability, and continuity in both bare-metal and cloud environments

• Technical leadership: Lead complex initiatives, establish technical direction, and influence engineering decisions across teams without relying on direct reporting authority

• Platform simplification: Identify opportunities to reduce operational complexity and consolidate the database and infrastructure technology footprint

• Automation: Design and implement automation for provisioning, configuration, deployment, upgrades, testing, maintenance, and database change management use cases

• Operational excellence: Establish durable practices for operating critical data infrastructure, including monitoring, incident response, capacity planning, maintenance, security, IAM, auditing, and traceability

• Performance engineering: Diagnose difficult performance and reliability problems across globally distributed, latency-sensitive infrastructure and drive issues through root cause to durable resolution

• Incident learning: Lead retrospectives and root-cause analysis for significant data-system incidents and convert findings into improvements to tooling, architecture, and operational practices

• Technical roadmap: Evaluate emerging technologies, develop roadmaps for the data platform, and communicate priorities and trade-offs across engineering and business stakeholders

• Mentorship: Raise the technical bar for engineers working with data infrastructure through architecture reviews, technical guidance, documentation, and hands-on collaboration

Tech Stack

• Databases & data systems: MySQL, MariaDB, Galera, PostgreSQL, Aerospike, Redis, Kafka, StarRocks, Vertica, Trino, Iceberg

• Infrastructure & orchestration: Kubernetes, bare metal, Terraform, Ansible

• CI/CD & deployment: Helm, GitLab workflows, ArgoCD

• Observability: Prometheus, Grafana, Loki

• Programming & automation: Python, Go, Bash/Shell, Kotlin, Java

• Adjacent data technologies: Kafka, Spark, Flink, Hadoop, Presto/Trino

Your Know-How

• You have 7+ years of experience spanning database reliability engineering, database administration, site reliability engineering focused on data systems, platform engineering, or a comparable infrastructure role

• You have operated large-scale production database systems where reliability, latency, availability, and performance genuinely matter

• You bring deep expertise with relational and distributed data systems and meaningful production experience with several technologies (such as MySQL, MariaDB, Galera, PostgreSQL, Kafka, Aerospike, Redis, StarRocks, or Vertica)

• You have experience deploying and operating stateful systems across Kubernetes and bare-metal infrastructure

• You understand relational data architecture and can make informed decisions around schema design, replication, availability, performance, scale, and continuity

• You have strong automation instincts and experience with infrastructure tooling such as Terraform, Ansible, Helm, GitLab CI/CD, ArgoCD, or comparable technologies

• You can automate infrastructure and operational workflows using Python, Go, Bash/Shell, Java, Kotlin, or another appropriate programming language

• You have experience building or operating effective observability systems (using technologies such as Prometheus, Grafana, Loki, or equivalent tooling)

• You understand database change management and have worked with tooling such as Liquibase, Flyway, Alembic, or similar systems

• You can troubleshoot complex failures across distributed infrastructure, reason from symptoms through multiple layers of a system, and identify root causes rather than treating symptoms

• You’re comfortable operating at “staff level” (aka setting direction, navigating ambiguity, mentoring other engineers, balancing immediate operational needs against long-term architecture, and influencing teams outside your immediate domain)

• You can communicate complex technical decisions clearly to both deeply technical colleagues and stakeholders without the same infrastructure background

It’s a bonus if

• You have experience operating databases across globally distributed, ultra-low-latency infrastructure

• You have meaningful experience with streaming and large-scale data technologies such as Kafka, Spark, Flink, Hadoop, Trino/Presto, or Iceberg

• You’ve operated infrastructure spanning both public cloud and privately operated data centres

• You have experience simplifying or consolidating a large database technology footprint without compromising reliability or developer productivity

• You have helped establish security, IAM, auditing, and traceability practices for critical data infrastructure

• You’ve worked in adtech, financial infrastructure, high-frequency systems, large-scale marketplaces, or another environment where extremely high transaction volume and low latency are fundamental engineering constraints