Sr. Database Reliability Engineer

The Team You Will Join 

At MetLife, our Database Infrastructure team within Global Infrastructure is dedicated to making a difference. We prioritize our customers' perspectives and continuously strive to enhance and simplify their experience. Whether you're focused on safeguarding our customers' and employees' data, developing top-tier database solutions, or utilizing data and analytics to transform insights into customer-centric solutions, your work has a significant impact. Each of us plays a crucial role in bringing MetLife's mission of building a more confident future to life. Interested in joining our team? We'd love to have you!

The Opportunity 

The Senior Database Reliability Engineer position is responsible for engineering and operating evolving database and logging platforms. This role involves managing and optimizing existing NoSQL and logging platforms globally, as well as evaluating and onboarding new database platforms and tools across the organization. This is an exciting opportunity to continuously improve stability and increase self-service through automation, self-healing, and AIOps, providing a best-in-class experience for our application development partners. An ideal candidate should have experience with various database platforms, data engineering, automation, DevOps, and infrastructure/configuration as code, and be able to contribute in multiple ways. 

Success in this role requires a forward-thinking individual who excels at managing data platforms using innovative methods, adapts quickly to new tools and technologies, and delivers what truly matters to customers.

How You’ll Help Us Build a Confident Future (Key Responsibilities)

• Leads and participates in efforts to leverage Automation, AIOps, and Observability for optimized data infrastructure performance, security, and stability, including research, planning, design, engineering, and operation of highly available, reliable, and scalable solutions.
• Designs and implement infrastructure-as-code solutions to build, configure, and manage database infrastructure.
• Develops and implements automation for self-healing mechanisms to minimize system downtime as well as self-service solutions for streamlined operations.
• Leads and participates in Root Cause Analysis (RCA) and recommends tuning and optimization procedures to improve database performance.
• Reviews and implements database configurations in alignment with MetLife data security standards.
• Demonstrates strong ownership and accountability.
• Participates in the on-call rotation to support a 24/7 environment.

What You Need to Succeed (Required Qualifications)

• Bachelor’s degree in computer science, Information Systems, or another related field or equivalent relevant experience.
• 5 years of experience in databases and database internals, with strong relational or non-relational database technologies or logging platforms (like Splunk). Examples for database technologies can include but are not limited to MongoDB, Oracle, SQL, PostgreSQL, Cassandra.
• Experience with Linux OS, and Cloud Platforms. 
• Experience with database programming and OS Scripting skills. 
• Extensive experience with data and database security. 
• Experience in Agile environments, with a solid understanding of Agile principles.
• Affinity to learn new technologies based on demand and help team members by coaching and assisting.

 What Can Give You an Edge (Additional Skills)

• Suggested 5 years of experience in IT and Infrastructure engineering work experience.
• Preference for candidates with non-relational database experience.
• Experience developing automation with Ansible.
• Azure DevOps preferred.
• Experience working closely with Observability tools like Elastic, Grafana, Datadog, Prometheus etc.
• Experience configuring and using APM tools. 
• MongoDB Certified DBA or Splunk Certified Administrator is a plus.
• Experience with PostgreSQL and Hadoop.
• Experience with database change management tools (Liquibase, Redgate, DB Maestro).
• Experience with API and API-driven development.
• Knowledge of Machine Learning (ML) and ML models, with experience in configuring ML jobs.