RAID Support Engineer

Advansys is a dynamic solutions provider focused on delivering smart, modular, and sustainable technology solutions that enhance operations, improve customer experiences, and drive business modernization. With over 400 skilled engineers, we serve 100+ enterprise customers across 14 countries. Specialized in a wide array of premium services including Business Automation, Industrial Digitization, Low code Development, Cloud Services, Warehouse Automation & Strategic Outsourcing.

Founded in 2014, Advansys is part of the INTRO Group, a private conglomerate established in 1980 with diverse investments across different business areas, oil and gas, real estate, specialized engineering, financial investment, Food & manufacturing.

We are looking for an experienced RAID Support Engineer who will be responsible for maintaining and troubleshooting our data management systems. In this role, you will provide support for complex SQL & PL/SQL issues, help with the performance tuning of Apache Spark jobs, monitor and manage Hive DB, and assist with Python-based automation and scripting. You will work closely with internal teams to ensure system availability, reliability, and optimal performance.

Job description:

• Provide technical support for RAID-related systems, resolving issues related to SQL & PL/SQL queries, Hive DB, Apache Spark jobs, and Python automation.
• Monitor system performance and proactively identify areas for optimization in data pipelines, SQL queries, and Spark jobs.
• Troubleshoot issues related to data systems, including Spark jobs, Hive DB, and SQL/PLSQL processes, ensuring minimal downtime.
• Work with the development and data engineering teams to implement bug fixes, performance enhancements, and system upgrades.
• Perform root cause analysis for recurring issues and implement long-term solutions.
• Support data integrations, ETL processes, and workflows, ensuring they run efficiently across systems.
• Assist in the automation of common support tasks using Python scripting and SQL automation.
• Manage and troubleshoot issues with distributed data processing platforms like Apache Spark, ensuring data jobs are running as expected.
• Document incidents, troubleshooting steps, and solutions to create knowledge base articles for internal teams.
• Collaborate with cross-functional teams including Data Engineers, Analysts, and Developers to provide timely and effective support.
• Assist with deployments and system upgrades, ensuring minimal disruption to ongoing operations.