Top Business Intelligence Jobs in Philadelphia, PA

Leads enterprise data architecture and infrastructure strategy, designing data warehouses, data lakes, and hybrid cloud solutions. Establishes governance, security, automation, DevOps, and CI/CD practices while evaluating emerging technologies such as AI and machine learning. Partners with executives and cross-functional teams on data strategy, cloud roadmaps, resource planning, cost optimization, integrations, and troubleshooting. Serves as an organization-wide subject matter expert and mentor.

Own and optimize the enterprise workforce management platform, including forecasting, scheduling, staffing, intraday performance, shift and PTO bidding, and schedule adherence. Analyze workforce and operational data, identify root causes, create trend and productivity reports, model ROI, and recommend staffing improvements. Partner with analytics and operations leaders, mentor real-time analysts and schedulers, and drive efficiency across service and clinical operations.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.

Senior Database Analyst/Administrator responsible for database architecture, administration, performance, security, data modeling, warehousing, ETL, migration, and data integrity. Develops SQL Server database objects, dimensional models, enterprise data marts, BI dashboards, and Splunk monitoring reports. Collaborates with stakeholders to translate business needs into technical requirements, supports Agile development, conducts code reviews, and implements cloud and hybrid-cloud database solutions.

Analyze insurance product and portfolio performance, build dashboards and reporting tools, validate data, and translate complex insurance questions into actionable recommendations. The role supports rate revisions, state expansion, product development, and profitable growth while partnering with Product, Engineering, Data, Underwriting, Compliance, and other teams. It also uses SQL, business intelligence platforms, and AI tools such as Claude to improve workflows and decision-making.

Develop business intelligence and revenue reporting tools, automate Finance reporting processes, perform ad hoc and quantitative analyses, and translate complex data into actionable insights. The analyst will support company initiatives, present findings to technical and non-technical stakeholders, and provide decision-making guidance across the organization.

Serve as the primary technical escalation point for managed services data and analytics clients. Troubleshoot and enhance Power BI, Fabric, Azure, and other analytics environments; gather requirements; translate business needs into scalable solutions; support client onboarding; maintain documentation; mentor support staff; and partner with client success and consulting teams. The role also contributes to continuous improvement, training, knowledge sharing, and AI-enabled productivity initiatives.

Looking for a Senior Business Analyst to gather requirements, collaborate with technical teams, and lead testing efforts, ensuring documentation and relationships are maintained with business teams.

Supports enterprise data governance and business intelligence for NAVSUP by profiling datasets, defining quality rules and business glossaries, validating metadata and lineage, reconciling API data, and tracking remediation. Develops test cases, dashboards, scorecards, reports, documentation, and training materials. Collaborates with data owners, stewards, engineers, and government stakeholders in Agile environments using Informatica, MuleSoft, Axon, Power BI, Azure DevOps, and AWS GovCloud.

Leads enterprise business intelligence, operational analytics, reporting, and process automation priorities. Partners with Operations, Product, Technology, and the Data & Analytics Platform team to translate business needs into clear requirements, shape data strategy, prioritize initiatives, and validate delivered solutions. Drives AI/ML-enabled automation, executive reporting, and decision-ready insights while influencing technology governance and investment roadmaps without owning platform engineering or architecture.

Design, build, and maintain Power BI dashboards and data models using Snowflake and other cloud sources. Collaborate with data engineers/ETL teams, gather stakeholder requirements, implement DAX and Power Query transformations, ensure data governance and performance, and deliver analytics within Agile processes.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

Contract PL/SQL developer to design and maintain Oracle PL/SQL code, perform ETL work, and support data warehousing and BI initiatives. Experience with Informatica, Teradata, and optionally Pentaho preferred. 6–12 month position based in Philadelphia.

Designs and delivers business intelligence solutions supporting quality, compliance, and operational processes. Translates clinical and operational requirements into technical specifications, builds datasets from EHR reporting databases using advanced SQL and visualization best practices, validates data, performs root-cause analysis, resolves reporting issues, and supports junior team members through knowledge sharing.

Designs, develops, and owns business intelligence dashboards, visualizations, analyses, and reporting solutions, primarily in TIBCO Spotfire and also Power BI. Responsibilities include data modeling, calculations, performance tuning, deployment workflows through GitHub, data quality collaboration, BI standards, risk identification, mentoring, and independent decision-making across a multi-tenant Life Sciences data platform.

Lead enterprise data architecture across multiple SaaS products by unifying reporting platforms, data models, and analytics capabilities. Assess current systems, define target-state architecture, establish data governance and quality standards, separate analytical workloads from transactional systems, and develop phased migration roadmaps. Guide database, engineering, and BI teams on cloud platforms, integration, modeling, performance, security, and reliability. Enable trusted cross-product reporting, governed self-service analytics, and data foundations for AI and advanced analytics.

Build and maintain performance dashboards, KPIs, and data frameworks for revenue operations. Analyze funnel performance and program effectiveness, translate complex data into leadership insights, automate recurring reporting, and perform SQL-based data wrangling and transformations. The role partners with cross-functional, engineering, and data science teams to improve measurement, resolve data issues, and support strategic business decisions.

Develops, publishes, schedules, and supports interactive Power BI reports, dashboards, datasets, and enterprise data models. Uses SQL, DAX, Azure, SSAS, AAS, and Microsoft Power Platform to analyze financial data, automate processes, implement schemas, gather requirements, and apply row-level security. Collaborates with BI teams and business users to improve reporting, data access, and decision-making.

Owns end-to-end development and maintenance of Tableau and Amazon QuickSight dashboards for operational and executive stakeholders. Translates business needs into datasets, visualizations, and actionable insights; writes SQL for analysis and validation; collaborates with data engineers on AWS lakehouse sources; optimizes performance, validates data quality, documents dashboards, and continuously improves the BI portfolio.

Supports Service Fund Operations by developing data solutions, ETL pipelines, reporting tools, and data models using SQL, Databricks, UDAP, Python, Power BI, and related platforms. Performs data analysis, troubleshooting, root cause analysis, user acceptance testing, and data migration support. Collaborates with business operations, IT, and provider relations to translate requirements into technical solutions and improve reporting and data quality.

Develop and distribute recurring reports, gather stakeholder requirements, enhance data and reporting capabilities, automate manual processes, analyze KPIs and trends, and present insights to business leaders. Partner with business and technical SMEs on data deep dives, quality improvements, and ad hoc finance and business initiatives. The role requires hands-on Power BI and SQL experience, strong Excel skills, and familiarity with VBA and Python.

Develops business intelligence applications and data models using Qlik, SQL, and related tools. Performs ETL, data validation, analytics process improvement, and impact analysis for reporting changes. Provides data-driven insights, supports audits and legislative inquiries, leads stakeholder meetings, and mentors teammates as a business intelligence subject matter expert.

Develops and maintains business intelligence applications, data models, reporting scripts, and analytics solutions using Qlik, SQL, and related tools. Imports data from multiple sources, validates data integrity, assesses downstream impacts, supports user testing, and collaborates with business stakeholders and IT to improve reporting processes and deliver actionable insights.

Designs and maintains executive dashboards, reports, semantic models, and automated analytics solutions using Power BI. Defines enterprise KPIs, data standards, and business rules while integrating data from ERP, CRM, manufacturing, SQL, and cloud systems. Partners cross-functionally with senior leaders to deliver insights, improve data quality, support master data management, and enable scalable self-service analytics and data-driven decision-making.