SQL Developer (Arlington)

Overview:

We are seeking a skilled SQL Developer to join our data team and play a key role in building, optimizing, and maintaining our data solutions. The ideal candidate will have strong SQL development experience, a solid background in data warehousing and data modeling, and proficiency in creating complex stored procedures. Familiarity with SSAS and Power BI is highly desirable, as this role will help bridge the gap between back-end data processes and front-end analytics.

Key Responsibilities:

• Design, develop, and maintain SQL queries, functions, triggers, and complex stored procedures.
• Support and enhance enterprise data warehouse structures, ensuring scalability and performance.
• Collaborate with business analysts and stakeholders to translate business needs into robust data models.
• Build and optimize ETL processes for data integration from multiple sources.
• Develop and maintain SSAS cubes and related analytical data models.
• Partner with reporting teams to design and support Power BI dashboards and reports.
• Monitor, troubleshoot, and optimize database performance and integrity.
• Ensure compliance with data governance, security, and quality standards.

Qualifications:

• Bachelors degree in Computer Science, Information Systems, or related field (or equivalent experience).
• Proven experience as a SQL Developer with strong T-SQL programming skills.
• Hands-on experience in data warehousing and dimensional data modeling.
• Proficiency in creating and optimizing complex stored procedures and SQL queries.
• Experience with SSAS (SQL Server Analysis Services), including cube design and deployment.
• Working knowledge of Power BI (or similar BI tools) for reporting and visualization.
• Strong understanding of ETL processes, data integration, and performance tuning.
• Excellent problem-solving, analytical, and communication skills.

Preferred Skills:

• Exposure to cloud platforms (Azure SQL, Synapse, AWS Redshift, etc.).
• Experience with SSIS or other ETL tools.
• Familiarity with Agile methodologies and DevOps practices for data projects.