Database and Data Loader Engineer - Automation Ops L2

About this role

Job Details: Job Description: We are seeking a Database and Data Loader Support Engineer to provide AO (Automation Operation) Level 2 technical support, troubleshooting, and maintenance for database systems and data loader processes as part of Data Analytics and Process Control (AO DAP) L2 team. This role focuses on ensuring smooth data operations, resolving technical issues, and supporting end-users with database and data integration challenges in an automated manufacturing environment. Qualifications: Bachelor's or Master's Degree in Computer Science, Information Technology or a related engineering field Minimum qualifications include: 3-5 years of experience in database engineering or database administration support Ability to work on-site in Kulim, Kedah, Malaysia with availability for 12-hour day shifts in a compressed 4-day work week schedule Highly flexible, results-oriented mindset with customer-first approach and ability to work in fast-paced, mission-critical Level 2 support environments Strong troubleshooting and analytical problem-solving abilities with excellent project management, verbal, and written communication skills Ability to resolve complex technical issues in high-pressure environments Understanding of Agile frameworks and ITIL/incident management processes Experience with relational database technologies Ability to follow procedures and work in a 24x7 support environment with previous support or operations experience Experience with automated monitoring and alerting systems Preferred qualifications: Proficiency in SQL query writing and optimization Experience with major database platforms (SQL Server, Oracle, MySQL, PostgreSQL database administration) Understanding of database concepts (tables, indexes, views, stored procedures) Knowledge of database backup and recovery procedures Familiarity with database monitoring tools and performance metrics Experience supporting databases on Linux and Windows Exposure to Oracle Real Application Clusters

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