Platform Database Engineer
Job description
About the role
The role manages MongoDB deployments in large scale cloud environments and applies SRE practices to data platforms. Database operations are coordinated with application and infrastructure teams to support enterprise services. You will own the design, implementation, and operational excellence of MongoDB platforms across hybrid cloud landscapes. This position requires deep collaboration with cross-functional partners to align data strategy with business objectives. You will drive standardization efforts that enhance reliability, security, and performance of database ecosystems. The work involves balancing tactical operational tasks with strategic improvements that scale with enterprise demand. You will translate complex infrastructure requirements into clear technical guidance for diverse stakeholders.
Key facts
What you'll do
Establish and enforce architecture standards for MongoDB deployments in large scale cloud and on premise environments.
Implement and optimize data platform resilience through defined strategies for high availability, disaster recovery, backup, restore, and multi region failover.
Collaborate with application teams to tune database performance and query execution across all phases of the software development lifecycle.
Design and apply access controls, auditing policies, and encryption mechanisms to satisfy enterprise security and compliance requirements.
Lead root cause analysis investigations and coordinate corrective and preventative actions for database incidents.
Mentor technical teams by providing guidance, conducting design reviews, and authoring standards and documentation.
Partner with infrastructure and application teams to ensure database platforms support reliable enterprise services.
Evaluate and integrate new database technologies and practices to improve observability and operational efficiency.
Serve as a technical authority during change management, release planning, and capacity forecasting activities.
Promote a culture of reliability by defining and monitoring key database health indicators and service level objectives.
Requirements
A minimum of 4 years of experience as a MongoDB DBA is required, including 4 years of administering MongoDB Atlas.
Experience with the AWS ecosystem, including EC2, EKS, CloudWatch, IAM, KMS, and VPC, is required.
Proficiency in Terraform, GitOps workflows, CI/CD automation, and containerized workloads on EKS or Kubernetes is required.
Experience with observability platforms such as Dynatrace, Prometheus, or similar tools is required.
Strong Linux administration skills and scripting abilities in Python and Bash are required.
Availability for on call rotation and participation in incident response is required.
Travel requirements include occasional travel as defined by company policy.
Candidates must be legally authorized to work in Argentina
Remote without sponsorship for this role.
Demonstrated experience managing database operations at scale is essential for success in this position.
Nice to have
Experience with Kafka, change data capture, and enterprise data integration platforms is preferred. Familiarity with GitOps practices and infrastructure observability at enterprise scale is preferred.
Practical notes
Remote work from Argentina
Remote is supported for this role.
On call rotation and incident response are part of the responsibilities.
Typical interview steps
Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.
Good to know
Database roles in cloud environments often combine engineering and operations responsibilities. MongoDB Atlas and AWS services are commonly used in enterprise platforms. Infrastructure as code and observability tools are standard practices for managing data platforms at scale.
Career growth
Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.