Job Summary
Storage Protocols & Basics Understand IO patterns on disks and how disk performance affects backup/recovery Knowledge of storage grouping constructs: appsets, hostsets, VVsets SAN Administration Understand and configure iSCSI, Fibre Channel (FC), and NVMe basics Export volumes/LUNs to hosts and create/format partitions in Linux/Windows environments Snapshot and Backup In-depth understanding of snapshot creation, management, and its role in backup strategies REST API Client Setup & API Fundamentals Install, configure, and use REST API clients (such as Postman, CURL, etc.) Understand RESTful methods: POST, PUT, PATCH, DELETE, GET, etc. Call Formation & Usage Formulate required API requests based on REST API specifications or documentation Interpret API responses and troubleshoot Operating Systems Windows and Linux Administration Basic OS installation, configuration, and troubleshooting for Windows and Linux Storage Connectivity & Multipathing Configure MPIO (Multi-Path IO), and set up FC/iSCSI LUN connections on both OS platforms Run and monitor disk I/O workloads on both operating systems Application Basics Install and configure common applications such as SQL Server, Oracle, etc. (optional but advantageous) Backup and Recovery Backup Types & Strategies Understanding of different types of backup: Full, Incremental, Differential, and Optimized backups Restore & Recovery Perform restores at file, volume, and VM levels Cloning & Copy Data Management Create and manage clones of backup data or production volumes VMware ESXi and vCenter Installation & Configuration Install and configure VMware ESXi hosts and vCente
Key Responsibilities
2. Collaborate with cross functional teams to design and implement automated testing frameworks.
3. Create test plans and test cases for etl and data warehouse testing.
4. Identify and troubleshoot issues in data transformations and data loading processes.
5. Conduct performance testing and ensure scalability of data pipelines.
6. Implement best practices for data quality assurance in etl environments.
Skill Requirements
2. Experience in automation testing of etl (extract, transform, load) processes and data warehousing.
3. Strong understanding of sql for data querying and validation.
4. Knowledge of big data technologies such as hadoop, spark, or kafka is a plus.
5. Familiarity with scripting languages like python, java, or shell scripting.
6. Excellent analytical and problem-solving skills with a keen attention to detail.
7. Ability to work collaboratively in a team environment and good communication skills.