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Job Description:
DataRobot delivers AI that maximizes impact and minimizes business risk. Our platform and applications integrate into core business processes so teams can develop, deliver, and govern AI at scale. DataRobot empowers practitioners to deliver predictive and generative AI, and enables leaders to secure their AI assets. Organizations worldwide rely on DataRobot for AI that makes sense for their business — today and in the future.
Datarobot is actively seeking a Database Engineer to join our Fleet Management team. This is a pivotal role that requires creativity, deep technical knowledge, and great enthusiasm to manage our stateful infrastructure.
This position is an exciting opportunity to own the full lifecycle (administration, automation, and troubleshooting) of our critical database systems operating within a large-scale, multi-tenant Kubernetes environment. You will be essential in driving our GitOps and Helm-centric deployment strategy, focusing on ensuring zero-downtime upgrades and maximizing performance and stability for our core platform services. This role offers the perfect opportunity to hone your skills and gain direct exposure to advanced cloud database architecture and container orchestration challenges.
Key Responsibilities:
Design, implement, and maintain database infrastructure using StatefulSets, Operators, and Helm charts to ensure databases are reliable, self-healing, and scalable.
Own the deployment lifecycle for database clusters by managing version control for Helm charts and configuration templates.
Support and administer production database systems by proactively instrumenting and monitoring performance, security, and availability within the containerized environment.
Perform zero-downtime upgrades and migrations for major and minor releases, developing and maintaining Helm hooks and custom scripts to automate complex stateful operations.
Manage and optimize performance for backend data stores, ensuring data consistency and integrity across pod life cycles.
Develop and maintain automated backup and recovery processes, specifically designed for containerized databases, including volume snapshots and off-cluster storage integrations.
Resolve critical production issues related to container resource limits, network policies, storage classes, and database-specific tuning/configuration within a Kubernetes cluster.
Partner with application teams to implement database changes, review migrations, and ensure efficient resource utilization in the shared Kubernetes infrastructure.
Develop and maintain automation tools and scripts (Bash, Python) specifically focused on simplifying Kubernetes management tasks, such as provisioning users/secrets and monitoring cluster state.
Knowledge, Skills & Abilities:
5 years of experience managing large-scale, high-availability database systems (PostgreSQL and MongoDB) in a SaaS environment.
Deep Expertise in Kubernetes & Helm (3+ years required):
Mandatory: Proven experience managing database deployments using Kubernetes and Helm deployments
Strong Proficiency: Experience defining, troubleshooting, and maintaining Kubernetes resources such as StatefulSets, Pod Security Contexts (SCCs), NetworkPolicy, and custom RBAC for database Service Accounts.
Deep knowledge of advanced PostgreSQL HA concepts (e.g., streaming replication, Repmgr/Patroni) and MongoDB sharding and replication, specifically how they are implemented and configured via Helm values.
Experience managing database infrastructure on major cloud platforms (AWS, GCP, or Azure).
Highly proficient in scripting (Bash/Python) and using GitOps principles to manage infrastructure and deployment pipelines.
Strong grasp of database performance tuning, scaling concepts, and optimizing SQL/Aggregation queries.
Container Orchestration Experience with production databases is mandatory.
Nice to have:
Hands on experience in using version control systems, configuration management tools and IaaC such as Terraform, CloudFormation
Experience using database tools such as pgAdmin, Pgbench, Robo3t, Studio3t, MongoDB Ops Manager and Mongo mirror
Experience with prometheus, cloudwatch and monitoring tools both within kubernetes and external cloud managed infrastructure
The talent and dedication of our employees are at the core of DataRobot ’s journey to be an iconic company. We strive to attract and retain the best talent by providing competitive pay and benefits with our employees’ well-being at the core. Here’s what your benefits package may include depending on your location and local legal requirements: Medical, Dental & Vision Insurance, Flexible Time Off Program, Paid Holidays, Paid Parental Leave, Global Employee Assistance Program (EAP) and more!
DataRobot Operating Principles:
Wow Our Customers
Set High Standards
Be Better Than Yesterday
Be Rigorous
Assume Positive Intent
Have the Tough Conversations
Be Better Together
Debate, Decide, Commit
Deliver Results
Overcommunicate
Research shows that many women only apply to jobs when they meet 100% of the qualifications while many men apply to jobs when they meet 60%. At DataRobot we encourage ALL candidates, especially women, people of color, LGBTQ+ identifying people, differently abled, and other people from marginalized groups to apply to our jobs, even if you do not check every box. We’d love to have a conversation with you and see if you might be a great fit.
DataRobot is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. DataRobot is committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. Please see the United States Department of Labor’s EEO poster and EEO poster supplement for additional information.
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