Top Remote Business Intelligence Jobs in Denver & Boulder, CO

Develops and maintains Power BI and Microsoft Power Platform solutions in secure government environments. Responsibilities include gathering requirements, analyzing data, creating visualizations and process models, coordinating enterprise platform initiatives, documenting systems, developing and executing test plans, troubleshooting issues, supporting deployments, and training end users. The role requires an active Secret clearance, security certification, extensive Power BI and Power Platform experience, and occasional travel under 10%.

Own Power BI datasets, semantic models, DAX measures, and dashboards end to end. Trace and troubleshoot data flows through Azure Data Factory, Microsoft Fabric, and Power BI while ensuring reporting accuracy. Partner with stakeholders to define requirements, document reporting logic, and expand self-service analytics. Use and validate AI tools for queries, DAX, documentation, and reporting automation. Develop broader Customer Operations systems knowledge over time.

Develop Power BI and Tableau dashboards, scalable data models, reporting solutions, automation workflows, and actionable analyses using financial, operational, Salesforce, RF, and video performance data. Monitor hybrid terrestrial and satellite delivery systems with tools such as Skyline DataMiner, identify trends and anomalies, and collaborate with stakeholders to deliver business intelligence solutions. The role requires strong communication, business acumen, SQL, Azure, XML, and ETL/ELT expertise.

Provides business intelligence consulting by gathering requirements, defining KPIs, and designing dashboards in Power BI and Amazon QuickSight. Builds data models, calculated measures, row-level security, and scalable reporting solutions; validates data quality and performance; documents metadata and lineage in Atlan; trains users; and collaborates with data engineers on data structures and pipelines.

Analyzes data from multiple sources to identify trends, develop member segmentation and lifecycle models, support competitive analysis, and recommend strategies for improving member participation and financial products. Builds reports, dashboards, and data-driven tools for leaders and staff, collaborates with stakeholders, trains power users, and provides ongoing analytical support using SQL, R or Python, ETL, data modeling, and business intelligence tools.

Owns Power BI reporting and analytics for Digital, including internal dashboards, campaign pacing, client-facing intelligence products, contact data health, and data delivery monitoring. Builds DAX reporting logic, automated alerts, budget tracking, segmentation, benchmarking, and trend analysis. Partners with IT, Data Engineering, CRM, and audience teams while transitioning an externally developed platform in-house. Serves as the senior reporting subject matter expert for stakeholder and client-facing analytics.

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.

Develop and manage enterprise Power BI dashboards, semantic models, data integrations, and automated reporting for global commercial operations. Analyze Salesforce and other business data using SQL and Python, support sales performance, territories, forecasting, compensation, and executive decision-making. Own reporting reliability, data quality, governance, troubleshooting, and documentation while partnering with Sales, Finance, Marketing, IT, and commercial leadership.

The Business Intelligence Engineer manages enterprise data sources, supports data quality and governance, and translates transactional data into KPIs for business teams. Responsibilities include guiding analyst teams, handling data inquiries, supporting advanced analytics, monitoring data performance, defining data requirements with stakeholders, and presenting findings to technical and non-technical audiences. The role requires SQL, Tableau, relational database, and data modeling or analytics expertise.

Build and maintain data pipelines, SQL queries, data models, database structures, and centralized data warehouse capabilities. Clean and validate data, develop reporting datasets and solutions, support KPI tracking and historical analysis, and collaborate with Finance and Revenue Operations. Investigate data gaps, troubleshoot integrations, and independently deliver reliable technical solutions.

Develops, validates, documents, deploys, and maintains Amazon QuickSight dashboards in a secure CMS environment. Translates stakeholder requirements into interactive visualizations, performs SQL-based ETL and data-quality validation, supports Tableau analytics, manages UAT and dashboard lifecycles, troubleshoots technical issues, and documents data workflows. The role collaborates with analysts, data scientists, CMS stakeholders, QIO staff, and other teams while supporting healthcare and regulated data initiatives.

Supports the development and maintenance of Qlik dashboards, reports, and data visualizations. Performs data analysis, validates reporting outputs, identifies trends and anomalies, translates business requirements into reporting solutions, troubleshoots data issues, and helps maintain metrics and KPIs. Collaborates with business stakeholders and develops knowledge of organizational data sources, business intelligence practices, and data governance standards.

Own executive, board, investor, financial, and operational reporting for leadership. Build scalable dashboards, define consistent KPIs, reconcile data across systems, investigate performance changes, and translate complex business questions into actionable insights. Partner with Strategy, Finance, and senior leaders to automate recurring reporting, improve data accuracy, and support actuals-versus-budget-versus-forecast analysis.

The Senior Data Analyst will develop and improve Sigma dashboards, reporting, and business intelligence capabilities. Responsibilities include gathering stakeholder requirements, querying and analyzing complex datasets with SQL, improving data quality and governance, defining metrics, automating reporting processes, and partnering on Snowflake data modeling and warehouse improvements. The role also evaluates analytics tools, delivers actionable insights, and communicates findings to technical and non-technical audiences.

Develop dashboards, reporting, and analytics solutions for business teams; monitor performance trends, data quality, risks, and key metrics; investigate complex questions; support A/B testing and instrumentation; and communicate actionable insights to technical and non-technical stakeholders. The role also requires expertise in profit drivers, unit economics, campaign and funnel performance, and the company’s analytics infrastructure.

Develop and maintain Power BI reports, dashboards, visualizations, semantic models, and analytics solutions. Translate business requirements into scalable technical solutions, optimize queries and data models, ensure reporting accuracy and performance, and support data governance. Serve as the primary liaison for business users, provide training and troubleshooting, manage tickets, and collaborate with Data and QA teams. The role also advances AI and machine learning capabilities, mentors colleagues, and contributes to automation, documentation, and code reviews.

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 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.

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.

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.

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.

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.

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.