Top Business Intelligence Jobs in Boston, MA

Lead the design, development, integration, optimization, and operational oversight of MicroStrategy analytics solutions supporting healthcare eligibility, claims, provider, member services, reporting, and financial workflows. Collaborate across technical and operational teams, drive modernization, resolve complex issues, coordinate data interoperability, manage vendors, and ensure secure, compliant, high-performing systems.

Supports the development and maintenance of BI dashboards, reports, data models, pipelines, and automated reporting processes. Writes SQL queries, cleans and validates data, analyzes business and operational trends, and translates findings into actionable insights. Collaborates with cross-functional stakeholders on reporting and analytics solutions while gaining experience with Power BI, data warehousing, Python, governance, and data quality practices.

Provides executive leadership for advancement analytics, business intelligence, reporting, data governance, integrations, data architecture, AI enablement, innovation, and organizational learning. Establishes data strategy and governance, oversees analytics and decision-support capabilities, leads directors and analysts, and partners with university stakeholders to improve fundraising effectiveness and organizational performance.

Lead and scale Runpod’s analytics and business intelligence function, managing analysts and BI practitioners while setting the analytics roadmap. Own core company metrics, consumption and marketplace analytics, self-service reporting, experimentation practices, and executive and board-level insights. Partner with Product, Finance, Engineering, Security, Supply, and Go-to-Market leaders to improve data quality, modeling, decision-making, and strategic outcomes.

The Business Intelligence Engineer analyzes complex internal and external data to solve business problems and deliver actionable insights to decision-makers. Responsibilities include integrating, analyzing, summarizing, and presenting data; conducting root cause analysis; using SQL, SAS, Databricks, and advanced Excel; and supporting data-driven business decisions. This is a remote role with occasional travel for training or meetings.

Lead a small business intelligence team while remaining hands-on with SQL, Power BI, reporting, forecasting, commercial analysis, and executive insights. Own the analytics roadmap, KPI frameworks, dashboards, data governance, and business logic. Partner with sales, marketing, executives, and data engineers to improve reporting and data quality. Mentor analysts and translate business questions into actionable recommendations for a B2B SaaS organization.

Leads enterprise Business Intelligence strategy, architecture, governance, security, and self-service analytics adoption. Architects solutions across Power BI, Tableau, SAP BusinessObjects, and Databricks; establishes semantic models, data standards, DevOps, CI/CD, and reporting performance practices. Partners with executives and technical teams to modernize analytics platforms, reduce manual reporting, and enable AI-ready decision-making. Mentors BI professionals and drives enterprise data literacy and analytics transformation.

The Business Intelligence Analyst queries cloud data, builds dashboards and recurring reports, validates data integrity, and delivers actionable insights to business leaders. The role embeds AI tools into reporting, documents data definitions and processes, automates manual work, and partners with FP&A, Business Operations, and Data Engineering. It requires SQL, Excel, BI reporting experience, and practical AI application, with Python, R, Git, and dbt listed as preferred skills.

Supports value-based healthcare programs through complex SQL analysis, reporting, data reconciliation, program evaluation, payment support, and ad hoc analytics. Works with healthcare and insurance data, develops monthly reports, evaluates new opportunities, and communicates findings to senior and executive leadership. The role requires advanced Excel and large-scale data experience, with preferred expertise in Azure Synapse Analytics, Databricks, PySpark, or Python.

Supports the Product Innovation Team by modifying and optimizing SQL queries, visualizing data with BI tools, identifying insights, and analyzing enhancements. Participates in coding, testing, documentation, and discussions while providing customer service and managing multiple tasks. The internship requires at least 30 hours per week and emphasizes advanced Excel and visualization skills, plus familiarity with Python and SQL.

Transforms complex retail and consumer data into business-ready datasets, scalable pipelines, reporting solutions, automation, and client deliverables. Designs data integration solutions in Unify, troubleshoots connector issues, explores AI-driven improvements, and partners with Product, Engineering, Client Development, Operations, and business stakeholders to define requirements and deliver scalable solutions.

Supports the Reporting and Insights team by developing data models, pipelines, dashboards, and ad hoc analyses. Responsibilities include SQL optimization, data validation, pipeline governance, requirements documentation, release management, stakeholder collaboration, and resolving business and technical issues across teams.

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.

Develop and maintain Power BI dashboards, reports, data models, and visualizations supporting commercial sales decisions. Translate business requirements into scalable analytics solutions, improve forecasting and performance reporting, troubleshoot data and reporting issues, validate releases, and maintain DataMart reliability. Partner with sales leaders, business analysts, stakeholders, and technical teams while following governance and development standards.

Develop and support enterprise BI solutions, including dashboards, reports, governed datasets, data marts, and ETL/ELT processes. Translate business requirements into technical designs, perform data analysis and validation, troubleshoot production issues, and maintain documentation, governance, security, and data-quality standards. Lead-level candidates will guide technical decisions, mentor team members, and coordinate complex initiatives and incidents.

Develop and maintain Power BI reports, dashboards, apps, and reusable semantic models using SQL, DAX, and Power Query. Own day-to-day Power BI platform operations, including workspaces, publishing, licensing, refreshes, gateways, permissions, and content lifecycle. Translate stakeholder requirements into decision-ready reporting experiences, validate data and calculations, support testing and releases, troubleshoot issues, and coordinate with engineering and security teams. Coach report authors and promote governed, reliable self-service analytics.

Lead CX data intelligence initiatives using SQL, dashboards, analytical models, and AI/LLM techniques. Analyze customer journeys, operational metrics, churn risks, and retention indicators; develop insight agents and self-service reporting; define CX health metrics; and translate findings into strategic recommendations, process improvements, and experiments. Partner with operations, support, product, data, and engineering teams while maintaining data quality, governance, and documentation.

Leads business intelligence, reporting, analytics, and project delivery initiatives. Partners with stakeholders and technical teams to gather requirements, define reporting solutions, manage timelines and risks, validate data and outputs, maintain dashboards, support testing and implementation, and identify process improvements. Uses complex data analysis, business process evaluation, and reporting expertise to improve operational performance, leadership decision-making, governance, automation, and consumer experiences.

Build and maintain reporting suites, dashboards, analytical models, and quantitative analyses that support business decisions. Partner with leaders across Operations, Risk, Servicing, Finance, Product, and Sales to investigate complex questions, generate actionable insights, and identify growth opportunities. Collaborate with data engineers to ensure accurate data delivery while managing multiple cross-functional projects and communicating findings through clear, persuasive narratives.

Build and maintain Tableau dashboards, KPIs, reports, forecasts, and business analyses for Customer Success, Marketing, and Sales. Query and validate cloud warehouse data using SQL, partner with Analytics Engineering on data models and quality, and translate stakeholder questions into actionable insights. Support self-service analytics, AI-enabled tools, documentation, training, and governance while analyzing pipeline, campaign performance, retention, churn, revenue, and customer data.

The Epic Business Intelligence Developer creates analytics content for Epic data, configures applications, writes SQL reports, and manages data models and analytics catalogs.

Leads business intelligence and database analysis to generate revenue insights, solve complex business problems, optimize digital performance, support sales and marketing initiatives, and develop predictive data products. The role requires advanced SQL analysis across large data warehouses, Tableau and web analytics reporting, data validation, executive presentations, and leadership of junior staff.

Build and maintain business intelligence models, dashboards, reports, and compensation analyses for shelter, breeder, and sales channels. Support insurance regulatory reporting, ad hoc analytics, data quality, governance, automation, and performance tuning. Partner with data engineering, compliance, and business teams to improve enterprise data models and enable AI-driven initiatives.

Develop and optimize SQL Server and SSIS billing pipelines, automate data movement and validation with Python, and use R and Python for analytics, anomaly detection, and billing decision models. Build data-quality frameworks, support internal reporting tools, integrate ERP APIs, and collaborate with finance and operations stakeholders. The role requires maintainable, tested, auditable solutions and ownership of features across databases, pipelines, analytics, and internal applications.

Lead business intelligence strategy across product, clinical, commercial, finance, and engineering teams. Build measurement frameworks, semantic layers, reporting solutions, and visualizations that demonstrate business value and support data-informed decisions. Own the data lifecycle from ideation through client-facing delivery, ensure data governance and integrity, and translate complex datasets into actionable insights. Collaborate on scalable data architecture and apply statistical methods, advanced analytics, and emerging AI-driven BI capabilities.