Top Senior Analysis Reporting Jobs in Baltimore, MD

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

Drive revenue operations analytics by building reliable data models and dashboards, querying large datasets in Snowflake, ensuring data integrity across the revenue tech stack, and delivering strategic insights to Sales, Marketing, and Customer Success using Looker, Domo, SQL, and scripting.

Provide insights and recommendations to improve end-to-end purchase customer journeys across web and app for B2C and B2B. Lead A/B testing and experimentation, ensure accurate data collection and impact measurement, build self-service reporting and visualizations, query and process data, and present findings to stakeholders and senior leadership.

Lead advanced analytics and predictive modeling to improve patient experience and drive financial outcomes. Collaborate with cross-functional teams to mine and analyze complex data, validate models, and present insights to senior leadership. Develop innovative analytical approaches to optimize digital products and programs, ensuring HIPAA-compliant remote work practices.

Design and deliver executive-ready Power BI reports, dashboards and agentic experiences. Build semantic models and self-service analytics, apply DAX, Power Query and Fabric notebooks, perform data exploration with SQL/KQL, and drive AI-enabled automation. Collaborate with data engineering to influence ingestion and transformation, translate business strategy into data solutions, and ensure performance, reliability, and scalability of reporting assets.

Lead workforce management strategy and operations for multi-brand contact centers. Manage WFM staff, forecasting, capacity planning, intraday operations, scheduling, analytics, and workforce technology (Genesys, Intradiem). Partner with Operations, Finance, Product, and vendors to drive process standardization, continuous improvement, and service-level attainment while implementing WFM tools and reporting across channels.

Partner with stakeholders to translate business needs into BI requirements, design and maintain BI solutions and semantic layers, analyze large payment datasets, enforce data governance and quality, deliver insights and reports, lead stakeholder meetings and training, mentor team members, and drive process improvements for data loading and analytics.

Document and reverse-engineer the client's ServiceNow data model and ITSM/CMDB processes. Design API-based incremental extraction into a Bronze layer and specify Bronze->Silver->Gold mappings. Define DNA crosswalk keys, data-quality gates and KPI confidence scoring, and support pipeline development, observability, and automated testing for ServiceNow as a source system.

Build and maintain batch ETL pipelines on Azure Databricks and Microsoft Fabric to ingest Workday and legacy systems into a governed medallion lakehouse. Develop Spark/Python/SQL transformations across Bronze/Silver/Gold layers, orchestrate and monitor workflows, implement data-quality checks, and model data for analytics. Lead-level engineers set standards, own complex integrations, mentor peers, and partner on platform and governance decisions.

Design and own a federated, multi-institution medallion lakehouse on Azure Databricks and Microsoft Fabric. Define federated multi-tenant architecture, Unity Catalog security, data ingestion from ERP/SIS/LMS/CRM/Workday, and platform standards. Provide hands-on architecture guidance, review designs, document decisions, and partner with governance, delivery, and engineering teams to enable production analytics at multiple institutions.

Support design, development, and implementation of a CMS-focused data warehouse program. Analyze and validate complex datasets, perform ad hoc and predictive analyses (including ML/fraud analytics), produce reports and metrics, provide QA and technical guidance, and streamline data processes using Excel, Power BI, Tableau, and SharePoint.