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MeridianLink

Database Engineer

US Remote (Remote)$114.6k–$155kfulltimemidAdded today

About this role

We're looking for an experienced Database Engineer to architect and manage enterprise data infrastructure spanning SQL Server, PostgreSQL, and MongoDB across cloud and on-premises environments. You'll optimize complex database systems, ensure high availability, and implement robust disaster recovery solutions.

What you'll do

  • Design, deploy, and optimize relational and NoSQL databases in multi-cloud and on-premises settings
  • Write and optimize complex SQL queries, stored procedures, and execution plans across multiple platforms
  • Develop and maintain backup, recovery, and disaster recovery procedures with RTO/RPO compliance validation
  • Monitor database performance, analyze metrics, and implement tuning and indexing strategies
  • Implement security controls, encryption, access management, and compliance standards
  • Manage database migrations, upgrades, and troubleshoot replication and clustering issues

What they're looking for

  • Microsoft SQL Server (2016+) with T-SQL, Always-On Availability Groups, mirroring, log shipping
  • PostgreSQL administration and optimization
  • MongoDB or NoSQL database design and management
  • AWS RDS and Aurora management
  • Backup/restore strategies and disaster recovery planning
  • Database security, encryption, and authentication
  • Performance tuning and index optimization
  • Cloud platforms (AWS, Azure)
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MeridianLink

MeridianLink builds a multi-product SaaS platform with foundational services for identity, authentication, and data integration. The company is hiring Software Engineers, AI Software Engineers, and Data Engineers to develop cloud-based solutions, scalable data pipelines, and platform infrastructure.

View all jobs at MeridianLink

Likely interview questions

  • Walk us through how you've designed and implemented a high-availability SQL Server solution using Always-On Availability Groups.
  • Describe your approach to troubleshooting a slow query and optimizing it through index strategies and execution plan analysis.