Database Engineer

Job Description

Job Description

Overview

CubeSmart is seeking an experienced Database Engineer specializing in cloud‑based database performance, optimization, and lifecycle management. This role is ideal for an engineer who excels at improving database performance at scale, designing and implementing archival solutions, executing complex patching and upgrade strategies, and ensuring the overall health and efficiency of PostgreSQL environments across cloud platforms.

You will partner closely with cloud Infrastructure, security, and application teams to ensure our PostgreSQL footprint is fast, stable, cost‑efficient, and aligned with cloud best practices.

Who we are:
At CubeSmart, we’re intentional about culture. You can experience it everywhere from our mission statement of “genuine care” to our “It’s What’s Inside That Counts” tagline to calling each other “teammates” rather than employees. This spirit fosters a fun and collaborative environment that has resulted in our rapid growth and being recognized amongst the top in our industry.

CubeSmart’s award-winning team is made up of people who genuinely care. Teammates care about our customers and the life events and/or business needs they are facing. Teammates are passionate, responsible and understanding. The CubeSmart team is made up of people who have a can-do attitude, are committed to their own success and the success of the company, and lead by example.

If this sounds like a team and culture that matches your personal values and motivations, we want to hear from you.

Responsibilities

Key Responsibilities

Cloud‑Native Database Engineering

• Architect, deploy, and manage PostgreSQL instances and clusters in cloud environments (AWS/Azure/GCP or managed solutions like RDS, Aurora, Azure Flexible Server, Cloud SQL).
• Develop cloud‑efficient database schemas, indexing strategies, and storage configurations.
• Optimize resource utilization (I/O, compute, storage tiers) to balance performance and cost.

Advanced Performance Tuning & Optimization

• Diagnose and resolve complex performance challenges using query analysis, indexing strategies, and execution plan optimization.
• Continuously tune PostgreSQL parameters (work_mem, shared_buffers, autovacuum tuning, WAL settings) to support high‑throughput workloads.
• Analyze pg_stat_activity, pg_stat_statements, and cloud native performance metrics to proactively detect and fix performance issues.
• Work closely with developers to optimize queries and improve data access patterns.

Archival Strategy & Data Lifecycle Management

• Define and implement a comprehensive data archival strategy to reduce resource consumption and improve performance.
• Architect cold storage, tiered storage, or partitioning-based archival solutions (e.g., native partitioning, time-based partition strategies).
• Automate archival, retention, and purging processes while ensuring compliance and auditability.
• Ensure archival strategies align with cloud cost optimization and long-term retention needs.

Database Maintenance, Patching, & Upgrades

• Develop and execute patching , minor version updates , and major upgrade strategies with minimal downtime.
• Implement blue/green or rolling upgrade patterns where supported.
• Ensure all PostgreSQL versions adhere to cloud provider support policies and internal governance.
• Maintain robust upgrade automation (Ansible, Terraform, CI/CD pipelines, or cloud-native tools).

Reliability, Monitoring & Operations

• Configure and tune monitoring and alerting for performance, replication health, vacuum performance, storage growth, and query latency.
• Ensure strong HA/DR strategies leveraging built‑in or cloud-native replication and failover mechanisms.
• Conduct capacity planning and performance forecasting to keep ahead of workload trends.
• Troubleshoot database incidents and drive root‑cause analysis for performance degradations.

Automation & DevOps Integration

• Automate provisioning, configuration, tuning, and lifecycle workflows using scripting (Python, Bash) and IaC tooling.
• Integrate database tasks into DevOps pipelines to support continuous deployment and automated patching.
• Build internal tools to improve operational consistency and visibility.

Qualifications

Qualifications

• 5+ years of production PostgreSQL engineering experience, including cloud deployments.
• Deep expertise in performance tuning, advanced query optimization, and PostgreSQL internals (WAL, MVCC, vacuum processes, query planner).
• Strong experience with cloud‑managed PostgreSQL platforms such as AWS RDS/Aurora, Azure PostgreSQL, or GCP Cloud SQL.  AWS RDS/Aurora is preferred.
• Hands‑on expertise with replication, failover, vacuum management, and HA strategies.
• Experience implementing data archival and lifecycle management practices at scale.
• Proven experience executing patching and major/minor PostgreSQL upgrades.
• Strong scripting skills in Bash or Python.
• Solid experience with monitoring tools (pg_stat_statements, Prometheus/Grafana, pganalyze, CloudWatch, Azure Monitor).
• Candidates must be authorized to work in the U.S. without the need for current or future sponsorship.

We are an Equal Opportunity Employer,  Minority/Female/Veteran/Individuals with Disabilities/Sexual Orientation/Gender Identity

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