Database Administrator

Project Role : Database Administrator Project Role Description : Design, implement and maintain databases. Install database management systems (DMBS). Develop procedures for day-to-day maintenance and problem resolution. Must have skills : Oracle Cloud Infrastructure Architecture Good to have skills : NA Minimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education

Database Administrator (DBA) - Mid-Senior Level Experience: 8–10 years Role Summary We are looking for a hands-on Database Administrator to join our team. In this role, you will own the day-to-day operations, performance, and reliability of our database fleet running on Kubernetes and cloud-native infrastructure. You will work closely with application and DevOps teams to ensure our data platforms are secure, scalable, and highly available. Key Responsibilities Administer, monitor, and tune production database systems across multiple environments (dev, UAT, staging, production). Perform schema design, privilege management, backup/restore, patching, and version upgrades. Operate databases deployed on Kubernetes using Helm charts, StatefulSets, and persistent volumes. Implement and maintain observability (metrics, logs, alerts) for database health and performance. Troubleshoot performance bottlenecks, query optimization issues, replication lag, and connection pooling problems. Support CI/CD pipelines by managing database changes through GitHub-based workflows. Collaborate with security teams on audits, encryption, IAM, and compliance requirements. Document runbooks, standard operating procedures, and incident postmortems.

Must-Have Skills 1. Strong hands-on Database expertise (SQL or NoSQL) 8+ years of hands-on administration of at least one enterprise database (PostgreSQL, MySQL, Oracle, SQL Server, MongoDB, Cassandra, Redis, or similar). Deep understanding of indexing strategies, query optimization, execution plans, and transaction isolation. Experience with backup and recovery strategies, point-in-time recovery, and high availability (replication, clustering, failover). Proficiency in user/role management, privilege models, and schema-level access control. Familiarity with connection pooling (PgBouncer, ProxySQL) and load balancing patterns. 2. Kubernetes Working knowledge of Kubernetes concepts: Pods, Deployments, StatefulSets, Services, ConfigMaps, Secrets, PVCs, and Namespaces. Experience running or supporting databases on Kubernetes using Helm charts or Operators. Comfortable with kubectl for troubleshooting, log inspection, and executing into pods for administrative tasks. Understanding of storage classes, persistent volumes, and stateful workload patterns. 3. Cloud Platforms (AWS preferred GCP or Azure acceptable) Hands-on experience with AWS services relevant to data workloads: RDS/Aurora, EKS, S3, IAM, KMS, CloudWatch, SSM Parameter Store, VPC, and Secrets Manager. Understanding of IRSA (IAM Roles for Service Accounts), security groups, and cloud networking basics. Experience with cost optimization, instance right-sizing, and reserved capacity planning. Familiarity with GCP (Cloud SQL, GKE) or Azure (Azure SQL, AKS) is a plus. 4. GitHub Proficient in Git workflows: branching, pull requests, code reviews, and merge strategies. Experience with GitHub Actions for CI/CD automation of database migrations, schema changes, and infrastructure updates. Comfortable managing configuration-as-code repositories and following GitOps principles.

Good-to-Have Skills 1. Terraform / Infrastructure as Code Ability to read, modify, and extend Terraform (or OpenTofu) modules for provisioning cloud resources, databases, IAM roles, and networking. Understanding of state management, workspaces, and module composition. 2. Database Architecture Awareness Exposure to designing multi-tenant schemas, sharding strategies, and read/write splitting. Familiarity with cross-database access patterns (foreign data wrappers, federated queries). Understanding of when to choose SQL vs NoSQL vs vector databases based on workload characteristics. 3. Additional Nice-to-Haves Scripting proficiency in Python, Bash, or PowerShell for automation. Exposure to observability stacks (Prometheus, Grafana, CloudWatch, Datadog). Familiarity with vector databases (Milvus, Pinecone) or graph databases (Neo4j, Memgraph).

15 years full time education

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