Microsoft SQL Server Administration

The Data Engineer is responsible for:

• Assessing data and application databases against the client's data retention schedules and recommending the appropriate retention schedule for various datasets.
• Developing and maintaining complex Microsoft SQL Server queries, stored procedures, and scripts to support data archiving, purging, and lifecycle management activities.
• Analyzing datasets to identify insights, trends, and data relationships, particularly in environments with limited or incomplete data dictionaries.
• Reviewing and optimizing SQL Server query performance , including indexing strategies, query tuning, and data processing enhancements.
• Supporting SQL-based ETL processes , including data extraction, transformation, loading, and validation using Microsoft SQL technologies.
• Documenting data processes, database logic, and workflows to ensure clarity, maintainability, and compliance with data governance standards.
• Collaborating with stakeholders and cross-functional teams to gather data requirements and deliver effective SQL-based solutions.
• Working independently while continuously building subject matter expertise in Microsoft SQL Server data management and optimization .
• Maintaining and enhancing technical proficiency by keeping current with best practices in SQL Server, data engineering, and database performance optimization .Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.

The ideal candidate should possess:

• Advanced proficiency in Microsoft SQL Server and SQL data analysis, including experience with complex queries, stored procedures, and performance tuning.
• Experience with SQL Server data modeling and relational database design.
• Intermediate experience in data engineering and data analysis within SQL Server environments.
• Strong analytical and problem-solving skills, with the ability to work effectively with complex datasets.
• Excellent communication skills and the ability to engage with clients and stakeholders, including facilitating discussions and meetings when required.
• A collaborative mindset, actively contributing solutions to technical challenges and supporting continuous improvement initiatives.

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