Oracle
Principal Consultant
Job Description
Key Responsibilities:
- Install, configure, upgrade, and patch Oracle database software (single instance and RAC environments).
- Administer and monitor database performance, capacity, and security using Oracle tools (OEM, Data Guard, RMAN, etc.).
- Implement and manage database backup/recovery procedures and disaster recovery strategies.
- Troubleshoot complex database, performance, and application-related issues.
- Plan and implement database migrations and upgrades.
- Automate routine database administration tasks using scripting (Shell, PL/SQL, Python, etc.).
- Develop and optimize database structures for AI workloads and analytics, enabling efficient data integration with AI/ML tools.
- Collaborate with data science, AI, and development teams to design and support AI-driven applications and analytics in Oracle environments.
- Implement and support Oracle features related to AI, such as Oracle Machine Learning (OML), and integrate with other AI/ML platforms as needed.
- Ensure data quality, security, and compliance in support of AI-driven automation and analytics initiatives.
- Maintain database documentation and adhere to security and compliance requirements.
- Mentor junior DBAs and provide 24x7 support for critical production systems as needed.
Qualifications:
- Bachelor’s degree in Computer Science, Information Technology, or related field.
- 5+ years’ experience as an Oracle DBA in mission-critical environments.
- Expertise in Oracle versions 12c/19c and experience with RAC and Data Guard.
- Strong knowledge of performance tuning, backup/recovery, and high availability.
- Experience working with AI/ML workflows, Oracle Machine Learning, or related analytics platforms.
- Proficient in SQL, PL/SQL, and Linux/Unix environments.
- Familiar with ITIL, change management, and incident management processes.
- Oracle Certified Professional (OCP) certification preferred.
Key Skills:
- Oracle RAC, Data Guard, OEM Cloud Control
- Oracle Machine Learning (OML) or experience supporting AI/ML workloads
- RMAN backup and recovery
- Database performance tuning
- Scripting (Shell, Python, etc.)
- Security, compliance, and auditing best practices
- Familiarity with data pipelines and AI/ML model integration
- Strong communication and documentation skills
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