Jamez Networks

Results-driven Senior Business Intelligence Analyst / BI Consultant with 7+ years of experience designing and delivering enterprise Business Intelligence, reporting, data analytics, and data integration solutions across healthcare, financial services, and consulting environments. Strong expertise in requirements gathering, stakeholder engagement, Power BI, SQL, DAX, Power Query, data modeling, ETL/ELT, Microsoft Fabric, Snowflake, Azure, Tableau, SSRS, and enterprise reporting. Proven ability to identify reporting inefficiencies, resolve data-quality issues, automate manual processes, and develop scalable dashboards and semantic models that improve operational visibility and executive decision-making.

Currently focused on modernizing BI development through Generative AI, Claude AI, MCP Server integrations, Microsoft Copilot, and AI-assisted Power BI development, while maintaining strong foundations in traditional BI architecture, data governance, performance optimization, and enterprise reporting.

Senior BI Consultant at ACCENTURE (2025-01 – Present)

• Led requirements-gathering sessions with executive, finance, operations, technology, and business stakeholders to identify reporting gaps, define KPIs, document business rules, and translate business problems into enterprise BI solutions.
• Identified fragmented reporting processes across multiple business units and redesigned reporting architecture using Power BI and Microsoft Fabric, improving enterprise KPI visibility by 40%.
• Designed and developed executive Power BI dashboards and scorecards covering operational performance, financial KPIs, productivity, service levels, and business performance, reducing management reporting time by 35%.
• Built scalable Star Schema and semantic models that standardized business logic and reusable measures, reducing duplicate report-development effort by 30%.
• Developed optimized T-SQL and Snowflake SQL, stored procedures, views, and transformation logic, reducing average report execution time by 40%.
• Implemented Incremental Refresh, optimized DAX measures, query folding, aggregations, and model optimization, reducing Power BI dataset refresh times by 45%.
• Integrated enterprise data from SQL Server, Snowflake, Azure SQL, SharePoint, Excel, and cloud applications, reducing manual reconciliation effort by 32%.
• Introduced Claude AI with MCP Server integration into BI development workflows to accelerate data-model analysis, DAX generation, calculated columns, SQL troubleshooting, documentation, and performance optimization, reducing development effort by approximately 30%.
• Leveraged Microsoft Fabric Copilot to accelerate semantic-model development, transformation logic, report generation, and analytical exploration, improving BI development productivity by 25%.
• Developed AI-assisted BI workflows that enabled analysts and developers to interact more efficiently with reporting datasets, troubleshoot calculations, and accelerate repetitive development activities.
• Automated recurring executive and operational reporting processes, eliminating manual Excel-based reporting activities and saving more than 30 analyst hours per month.
• Established data-quality and reconciliation frameworks that identified inconsistencies between source systems and reporting datasets, reducing recurring reporting discrepancies by 35%.
• Implemented Power BI Service governance, Row-Level Security, workspace management, deployment pipelines, gateway configuration, and scheduled refreshes to improve security and reporting reliability.
• Partnered with Data Engineering teams to troubleshoot ETL failures, data-quality issues, and pipeline bottlenecks, reducing recurring reporting incidents by 28%.
• Authored business requirements, technical specifications, data dictionaries, KPI definitions, transformation documentation, report specifications, and user guides, while conducting UAT, stakeholder demonstrations, end-user training, and final knowledge-transfer sessions.

Senior Business Intelligence Analyst at OSCAR HEALTH (2023-10 – 2024-12)

• Led requirements-gathering workshops with healthcare finance, revenue-cycle, operations, and executive stakeholders to identify reporting challenges and define KPIs for enterprise healthcare analytics.
• Identified fragmented revenue-cycle reporting processes and developed centralized Power BI dashboards covering Accounts Receivable, denials, charge lag, work queues, collections, and operational performance.
• Designed healthcare KPI dashboards that improved visibility into operational bottlenecks by 40% and enabled management to identify underperforming processes faster.
• Integrated data from SQL Server, Snowflake, healthcare applications, Excel, and enterprise platforms, reducing manual reporting and reconciliation activities by 30%.
• Built enterprise Power BI semantic models using Star Schema principles, reusable measures, dimensional modeling, and standardized KPI definitions, reducing report-development effort by 30%.
• Developed complex DAX calculations and Power Query transformations supporting financial, operational, and revenue-cycle analytics.
• Optimized SQL queries, stored procedures, and data-extraction processes, improving data retrieval performance by 40%.
• Implemented Incremental Refresh, query optimization, and Power BI performance-tuning techniques, reducing dataset refresh times by 45% and improving dashboard responsiveness.
• Standardized reporting definitions across multiple healthcare data sources, improving KPI consistency by 35%.
• Conducted data profiling, validation, and reconciliation across healthcare systems, reducing recurring data-quality issues by 32%.
• Developed operational dashboards for AR aging, denial trends, charge lag, productivity, work queues, and revenue-cycle performance, enabling managers to identify exceptions and prioritize corrective action.
• Implemented Power BI workspace governance, Row-Level Security, scheduled refreshes, deployment processes, and secure report distribution for sensitive healthcare information.
• Collaborated with Data Engineers and application teams to resolve ETL, source-system, and data-quality issues, improving reporting reliability by 28%.
• Participated in UAT, sprint planning, backlog refinement, stakeholder demonstrations, and production releases within Agile delivery teams.
• Prepared technical documentation, data dictionaries, KPI definitions, UAT documentation, report specifications, transformation logic, and training materials, followed by dashboard walkthroughs and end-user training.

Senior Data Analyst at TD BANK (2021-01 – 2023-09)

• Led requirements-gathering sessions with lending, operations, underwriting, risk, product, and executive stakeholders to define BI requirements across the consumer lending lifecycle.
• Identified bottlenecks in loan applications, underwriting, closing, and funding processes and developed centralized BI solutions that contributed to a 22% reduction in processing turnaround time.
• Designed enterprise Power BI dashboards monitoring application volume, approval rate, underwriting TAT, funding rate, pipeline aging, delinquency, portfolio growth, and productivity.
• Developed executive scorecards that provided leadership with improved visibility into lending performance and operational bottlenecks.
• Built reusable Star Schema data models and enterprise reporting datasets, reducing duplicate report-development effort by 30%.
• Developed optimized T-SQL queries, stored procedures, views, and reporting datasets, reducing report execution time by 40%.
• Automated daily and monthly lending performance reporting, eliminating manual Excel reporting processes and saving approximately 25 analyst hours per month.
• Created dashboards for application backlogs, SLA compliance, funding conversion, exception volumes, credit decisions, and pipeline aging, improving operational response time by 27%.
• Developed productivity dashboards for Underwriters and Loan Officers, contributing to an 18% improvement in team productivity.
• Implemented Incremental Refresh, optimized DAX calculations, query optimization, and data-model redesign, reducing Power BI refresh times by 45%.
• Integrated data from SQL Server, Azure SQL Database, SharePoint, and enterprise lending platforms, improving reporting accuracy by 28%.
• Conducted data profiling, reconciliation, and quality assurance across lending systems, reducing data-quality issues by 35%.
• Managed Power BI Service workspaces, gateways, scheduled refreshes, deployment pipelines, and Row-Level Security for sensitive financial data.
• Collaborated with Product Owners, Business Analysts, QA teams, and Data Engineers in an Agile/Scrum environment, completing approximately 95% of sprint deliverables within agreed timelines.
• Produced technical documentation, KPI definitions, data dictionaries, report specifications, UAT materials, and training documentation, and delivered dashboard walkthroughs and end-user training that reduced ad-hoc reporting requests.