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.

• Familiarity with big data technologies (e.g., Hadoop, Kafka, etc.).
• Experience with Linux
• Knowledge of data warehousing and data storage solutions.
• Experience in creating automated reports and performance metrics.
• Previous experience in customer-facing support roles or IT support engineering.

- Hybrid Working Model

- Social and Medical insurance

- Flexible and Friendly working environment