Permanent
Posted on 04 June 25 by Adina Baudun
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Our client is seeking a Senior Database Administrator to support and enhance their enterprise data architecture. This individual will be responsible for delivering secure, scalable, and high-performance data solutions that bridge both on-premises and cloud environments. This is a hands-on role ideal for professionals with a strong foundation in SQL Server database administration, hybrid architecture, and end-to-end data pipeline development. The successful candidate will join a collaborative team working on strategic data initiatives that support organizational growth and innovation.
Design, implement, and maintain relational database systems, focusing on SQL Server environments with a strong emphasis on on-prem administration and optimization.
Manage database security, integrity, backup, and disaster recovery across hybrid infrastructures (on-prem/cloud).
Build and maintain data pipelines to support data ingestion, transformation, and integration between enterprise systems.
Develop and enforce best practices in database design, code quality, and change management for data architecture.
Monitor and troubleshoot system performance; proactively resolve data quality or access issues.
Lead or contribute to infrastructure and data initiatives, managing timelines, deliverables, and stakeholder communication.
Collaborate with cross-functional teams including applications, infrastructure, and analytics teams to deliver scalable solutions.
Evaluate and recommend technologies for cloud transition, performance monitoring, and automation.
Proven experience with Microsoft SQL Server, including administration, performance tuning, and security.
Hands-on expertise with database administration (DBA) tasks including backup/recovery, patching, and availability management.
Strong experience in hybrid environments, working across on-premise and cloud platforms (e.g., Azure, AWS).
Exposure to PeopleSoft systems and integration strategies.
Familiarity with Python, especially for scripting and data automation tasks.
Background in or exposure to data science, including analytics, statistical modeling, or data visualization tools.
Experience conducting or participating in code reviews for database objects or ETL workflows.
Ability to independently assess and resolve complex data challenges in production environments.