Database Engineering

Job Description

REQUIREMENTS

• Hands-on software development experience in Java and Python — building production-quality tooling and platform services, not just scripting.
• Production experience with relational databases (MySQL, AWS RDS) — including performance tuning, query optimization, replication, backup/restore, and patching.
• Hands-on experience with the AWS ecosystem (EC2, ECS, RDS, S3, Lambda, CloudWatch, IAM, VPC) and IaC tools (CloudFormation, Terraform, Ansible).
• Experience with CI/CD pipelines (Jenkins, Bitbucket Pipelines) and container orchestration (Docker, ECS, Kubernetes/EKS).
• Strong networking fundamentals (TCP/IP, DNS, HTTP/S, load balancers, security groups) as applied to application and database connectivity.
• Familiarity with developer frameworks (Spring Boot, microservices, API design), Git-based version control, and Bash/Python scripting for automation.
• Demonstrated fluency with AI-assisted development tools for debugging, code generation, and accelerating problem-solving at scale.
• Proven ability to collaborate across engineering, DevOps, and DBA teams with working knowledge of ITIL practices and service management tools (ServiceNow).

RESPONSIBILTIES

• Design and maintain internal tooling, automation frameworks, and platform services using Java and Python.
• Architect and manage database platforms (MySQL, AWS RDS, NoSQL) with a focus on high availability, disaster recovery, and performance at scale.
• Build CI/CD pipelines that automate schema changes, application deployments, and infrastructure provisioning using Jenkins, Bitbucket Pipelines, and GitOps workflows.
• Monitor, tune, and optimize database performance — including query optimization, indexing, replication health, and capacity planning.
• Manage Infrastructure as Code (CloudFormation, Terraform, Ansible) to support consistent and scalable provisioning across environments.
• Design and support containerized workloads on Kubernetes (EKS), bridging application teams and the infrastructure that serves them.
• Own database change delivery and promotion across environments with zero-tolerance for production risk.
• Apply AI-assisted development tools for debugging, code generation, automation, and root-cause analysis across the full stack.
• Collaborate across engineering, DevOps, and DBA teams on architectural decisions spanning application design, data platform strategy, and operational excellence.

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