Senior DataOps Automation Engineer

Role & responsibilities

Design and own end-to-end Jenkins automation for database/environment refreshes, quarterly patching, releases, credential rotation, archival, and backup validation.

• Orchestrate cross-system dependencies, application/database stop-start, health checks, failover preparation, and controlled production execution.
• Develop reusable AI skills/agents for database pull-request and DDL validation, on-call triage, operational checks, and guided remediation.
• Enable self-service for DevOps and Release Management through approvals, access controls, audit trails, robust exception handling, recovery procedures, and runbooks.
• Integrate database automation with GitHub, AWS services, monitoring, incident management, and enterprise secrets management.

Preferred candidate profile

7+ years in database, platform, or automation engineering, with demonstrated ownership of production automation solutions.

• Strong Oracle and PostgreSQL knowledge, including database security, backup/recovery, high availability, troubleshooting, and AWS RDS/Aurora PostgreSQL.
• Advanced Jenkins Pipeline-as-Code skills, including Groovy, reusable shared libraries, parameterized pipelines, environment promotion, validation gates, and rollback/error handling.
• Strong Python, Bash/Shell, and SQL skills; experience with Git/GitHub, pull requests, REST APIs, and CI/CD integrations.
• Hands-on AWS automation experience involving RDS/Aurora, IAM, Secrets Manager, CloudWatch, and secure credential handling.
• Practical ability to build AI-assisted skills or agent workflows that use tools/APIs (including MCP-style integrations), enforce guardrails, and require human approval for sensitive production actions.
• Sound understanding of production change management, least-privilege access, auditability, idempotency, retries, and operational resilience.

PREFERRED EXPERIENCE:

• Delphix, Oracle RAC/Data Guard/RMAN, environment refresh orchestration, archival, or HA/failover operations.
• ServiceNow, Jira, Dynatrace, Terraform, AWS CDK/CloudFormation, or similar enterprise automation tooling.
• Experience developing self-service platform capabilities or using Claude Code, Amazon Q Developer, or comparable AI-assisted engineering tools.