Senior Data Solutions Analyst

Type: Permanent / Direct Hire / Full Time Senior Data Solutions Analyst (SQL, Power BI, Data Engineering & AI) Required Qualifications 5+ years of professional experience in application development with significant data responsibilities. Advanced SQL skills (complex queries, performance tuning, indexing concepts, and database object development). Demonstrated SSRS and SSIS experience. Strong Power BI experience (data modeling, DAX, Power Query, performance optimization). Experience with modern front-end frameworks/libraries such as React (or equivalent). Preferred Qualifications Experience with data warehouse/analytics engineering (dimensional modeling, curated datasets, governed semantic layers). Experience building and integrating REST APIs and system-to-system integrations. Experience with Microsoft Power Platform (Power Apps / Power Automate) and related development patterns. Experience developing and integrating SPFx web parts and/or Power Apps Component Framework (PCF) components. Experience with DevOps practices and automation tooling (e.g., Azure DevOps) and scripting (e.g., PowerShell). Experience with version control (e.g., Git) and Agile delivery practices. Familiarity with AI concepts and enterprise AI tooling, including implementing secure, governed AI-enabled solutions. Manufacturing/distribution business process experience (inventory, purchasing, logistics, order lifecycle) is a plus. Key Responsibilities Design, build, and optimize Power BI datasets, semantic models, dashboards, and reports using industry best practices. Develop DAX measures and Power Query transformations while optimizing report performance and user experience. Partner with business stakeholders to define KPIs and ensure consistent calculation logic across enterprise reporting. Support report publishing, security, access controls, and governance for enterprise reporting solutions. Data Solution Development Design, develop, test, deploy, and maintain data-driven business solutions using modern engineering practices. Build and enhance data applications, APIs, reporting solutions, and system integrations. Write clean, maintainable, and efficient code while participating in code reviews and contributing to development standards. Collaborate with business stakeholders to translate reporting and analytics requirements into scalable technical solutions. Develop and optimize complex T-SQL objects including stored procedures, views, and functions while performing query performance tuning and indexing. Engineer reliable data pipelines for ingestion, transformation, validation, and orchestration with appropriate logging and monitoring. Troubleshoot data integration issues while ensuring data accuracy, integrity, consistency, and auditability. Create and maintain technical documentation for databases, ETL pipelines, integrations, and data interfaces. Data Warehouse & Analytics Engineering Design and maintain analytics-ready datasets, dimensional models, and governed semantic layers. Establish and enforce standards for metric definitions, dataset reuse, refresh schedules, and enterprise data documentation. Improve data quality, reliability, and availability through validation routines and automated quality checks. Identify and implement AI-assisted opportunities within analytics and data workflows (e.g., summarization, anomaly detection, intelligent search, guided insights). Apply responsible AI practices, including validation, governance alignment, and human-in-the-loop controls where appropriate. Contribute reusable design patterns for secure and governed AI integration into enterprise business processes. Operational Excellence & Support Provide production support, perform root cause analysis, and implement permanent solutions for data and reporting issues. Maintain runbooks, technical documentation, deployment procedures, and operational support documentation. Mentor junior developers and analysts while contributing to overall team capability and knowledge sharing. #J-18808-Ljbffr