REQUIRED QUALIFICATIONS:

• Bachelor’s degree in Computer Science, Information Technology, or a related field.
• Minimum of 5 years’ experience as a SQL Server Database Administrator.
• Professional experience with Microsoft SQL Server 2016, 2017, 2019, or newer.
• Strong knowledge of SQL Server high availability and disaster recovery technologies.
• Solid understanding of performance tuning, query optimization, and index strategies.
• Hands-on experience with Azure SQL databases and patch/update procedures.
• Familiarity with other database platforms such as MySQL, Oracle, PostgreSQL, and MongoDB is a plus.
• Proficiency in scripting (e.g., T-SQL, PowerShell) for maintenance and automation.
• Strong troubleshooting and analytical skills across infrastructure layers.
• Excellent documentation and communication abilities.
• Microsoft SQL Server Certification (e.g., Microsoft Certified: Azure Database Administrator Associate) is required.

Additional Locations:

• Singapore - Central Singapore - Singapore
• Singapore - Central Singapore - SINGAPORE
• Singapore

• Singapore - Central Singapore

• Singapore - Central Singapore - Singapore , * Singapore - Central Singapore - SINGAPOR

• Managed Windows Servers (Wintel) in AWS, overseeing the deployment, configuration, and ongoing management of cloud-based virtual machines (VMs) and instances.
• Design, develop, and maintain SQL queries, stored procedures, functions, and triggers.
• Optimize database performance through indexing, query tuning, and schema design.
• Collaborate with data analysts, software developers, and business stakeholders to understand data requirements.
• Develop ETL processes to extract, transform, and load data from various sources.
• Ensure data accuracy, consistency, and security across all database systems.
• Create and maintain documentation related to database structures, processes, and standards.
• Troubleshoot and resolve database-related issues and provide ongoing support.
• Designed large scale cloud migration on data warehousing and data lake house projects
• Developing and debugging cloud-based data assets. Creating ETL jobs.
• Drive analytics team to identify various opportunities to automate reporting and providing meaningful Data
• Implemented and Design & Build Data Pipelines: Develop and optimize ETL/ELT workflows to ingest, process, and transform large datasets.
• Data Warehousing & Modeling: Design and maintain data warehouses and implement efficient data models.
• Cloud & Infrastructure: Deploy and manage data solutions on cloud platforms (AWS, Azure) using services like S3, Databricks etc.
• Data Quality & Governance: Ensure data accuracy, consistency, and security through monitoring, validation, and governance practices.
• Collaboration: Work closely with data scientists, analysts, and business teams to understand data requirements and deliver scalable solutions.
• Performance Optimization: Improve query performance, reduce latency, and enhance system reliability.
• Automation & CI/CD: Implement automation for data workflows and integrate with DevOps