Microsoft SQL Server Database Analyst

Job PurposeThe Microsoft SQL Server Database Analyst is responsible for developing, deploying, and optimizing SQL Server queries, managing data modeling workflows, and building Power BI reports for internal and client projects. The Analyst collaborates with stakeholders, solutions architects, and developers to deliver impactful analytics, leveraging manufacturing ERP data (strongly preferred Sage 500 ERP experience) to enhance performance management, profitability, and manufacturing efficiency analyses. The Analyst will also integrate AI-assisted coding tools (Amazon Q Developer, GitHub Copilot, etc.) into workflow processes to maximize productivity. The Analyst is responsible for robust documentation, daily communication, and remote collaboration, ensuring clarity and transparency in delivery. Responsibilities Develop Understanding of Business Context: The Database Analyst is responsible for reviewing analytics and reporting requests thoroughly, actively raising questions to understand the underlying business objectives and required analytical insights. Development Estimates: Works closely with Solutions Architects and stakeholders to provide comprehensive estimates, identify and mitigate risks proactively, and ensure accurate, timely delivery of data analysis and reporting tasks. Development Estimate Risk: Analyst must effectively communicate any potential deviation from original estimates promptly upon identification. SQL Server Development: Develops and optimizes SQL queries, stored procedures, and database models, adhering to Microsoft SQL Server best practices, ensuring performance, security, and maintainability. Understands on-prem SQL Server deployment standards and performance management practices, employing efficient query design, indexing strategies, and proper normalization techniques. Power BI Development: Builds, maintains, and refines highly effective, visually compelling dashboards and reports in Power BI, utilizing DAX formulas, Power Query transformations, and advanced data visualization techniques. Technical Architecture: Delivers succinct summaries of the technical architecture and analytical approaches for complex Epics or Stories as needed, clearly documenting ERP data modeling strategies and analytics workflows. AI-assisted Development: Integrates AI-driven coding assistance tools (e.g., Amazon Q Developer, GitHub Copilot) into SQL Server and Power BI workflows to enhance productivity, code quality, and analytical insights. Release Management: Responsible for reviewing, testing, documenting release notes, and deploying analytical solutions into production environments. Ensures smooth, stable deployments with minimal risk. DevOps: Adopts Facet's current data engineering, deployment, and local development standards, continuously improving and optimizing operations across the analytics portfolio, particularly leveraging automation, linters (e.g., sqlfluff), and other best practices. Standard Operating Procedures (SOPs): Demonstrates in-depth understanding of Facet's analytics and development SOPs, contributes actively to SOP refinement, and consistently produces detailed documentation to build organizational knowledge. Risk Management: Collaborates with principals and technical architects to proactively identify, document, and address analytical, technical debt, or operational risks. Actively participates in ticket grooming for upcoming work. Outcomes: Specific Measures of Success 90% Standardization of SQL Server and Power BI Deployment Operations across all client and internal projects within 3 months. 50%+ Reduction in manual intervention for recurring reporting tasks through effective use of automation and AI-assisted tools within 6 months. Establish a robust manufacturing-focused analytics framework (especially with Sage 500 ERP), driving measurable improvements in profitability, cost-based analysis accuracy, and manufacturing efficiency. Reduce overall project delivery timelines through improved documentation, communication, and analytics standardization.