Senior Data Solutions Analyst

Type:
Permanent / Direct Hire / Full Time

Senior Data Solutions Analyst (SQL, Power BI, Data Engineering & AI)

• 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).

• 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 Dev Ops practices and automation tooling (e.g., Azure Dev Ops) and scripting (e.g., Power Shell).
• 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.

• 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.

• 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.

• 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.

• 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.