Top Data Analyst Jobs in Denver & Boulder, CO

Validate and review CO APCD-derived data products using SQL and visualization tools, perform output comparisons and project-level analyses, follow quality control standards, document findings, and communicate results to technical and non-technical stakeholders while supporting continuous improvement of data QA processes.

Lead data strategy and analytics for Compliance and AML, develop ETL and validations, quantify regulatory risk, communicate insights to stakeholders and regulators, and drive cross-functional compliance initiatives.

Support Finance and Sales by reconciling and validating revenue KPIs (ACV, ARR, renewals), building reporting datasets and dashboards, collaborating with CRM and data engineering teams, and participating in month-end and quarter-end close activities. Provide ad-hoc analysis and stakeholder-facing explanations of metric derivation and data quality.

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Lead data analyst responsible for advanced analytics, real-time performance dashboards, network capacity modeling, and generating actionable insights for third-party service providers. Drives testing and pilots, analyzes stakeholder feedback, and serves as an internal analytics subject-matter expert to inform network strategy and operational improvements.

Analyze transactional metrics to identify inefficiencies, financial risks, and fraud; produce and validate daily/weekly/monthly reports and proactive alerts; consolidate and validate data sources for reporting; recommend process improvements to improve collections efficiency and customer satisfaction; deliver presentations and special-project analyses to senior management while leveraging automation and AI tools.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

As a Lead Data Science Analyst, you will develop predictive models, perform statistical analyses, and implement AI-driven solutions to enhance the sales customer lifecycle and drive business insights.

Own operational data pipelines, dashboards, reports, and analytical requests across customer experience, fraud, payments, workforce management, and VIP operations. Surface trends, anomalies, risks, and actionable recommendations; improve data quality and automate manual reporting. Partner with Data Engineering on dbt and data infrastructure, support AI agent initiatives, measure post-deployment performance, and identify opportunities to apply AI to analytics workflows.

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.

Support analytics by cleaning, validating, and transforming data; build dashboards and KPI reports; perform trend, cohort, and A/B testing analyses; improve data pipelines and forecasting; present insights to cross-functional teams.

Leads advanced data analysis to guide product and business decisions, develops metrics, dashboards, data products, and AI-enabled reporting systems, and translates findings into strategic recommendations. Partners with data engineers on dimensional data models, data governance, and quality controls. Mentors analysts, aligns roadmaps with business priorities, improves problem framing, and communicates insights effectively to technical and business stakeholders.

Analyze large healthcare datasets and develop complex SQL queries using Azure Synapse/Databricks. Build Power BI reports, produce monthly reconciliations and ad-hoc analyses in Excel/PowerPoint, support payments to value-based specialists, evaluate and expand value-based programs, automate processes with Power Automate/Power Apps, and communicate findings to senior leadership while spearheading new technologies.

Collects, validates, analyzes, and transforms perioperative, financial, and statistical data for recurring and ad hoc reports. Develops and maintains databases, spreadsheets, dashboards, and block-utilization analyses; identifies trends and recommends operational improvements. Collaborates with administration, physicians, Information Services, and Analytics teams, presents findings, supports reporting methodologies, and manages assigned surgery system updates.

The Data Analyst gathers and documents data requirements, queries and analyzes data, validates reporting outputs, and supports KPI tracking. The role researches data sources, assists with ETL and enterprise data warehouse integration, maintains data dictionaries and lineage documentation, identifies quality issues, and delivers reports and insights to stakeholders. Additional responsibilities include supporting data governance, PII controls, master data management, reporting automation, and cross-functional solution design.

Analyze workforce data and develop HR dashboards, scorecards, KPIs, visualizations, and automated reporting solutions. Identify trends across the employee lifecycle, evaluate engagement and employee programs, ensure data quality and compliance, and provide actionable recommendations to HR and business leaders. The role also supports employee listening strategies, reporting process improvement, data governance, and executive-level presentations.

Support marketing analytics by analyzing digital channel performance, building and maintaining KPI dashboards, ensuring data accuracy, and collaborating with cross-functional teams to turn insights into actionable recommendations.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.

Design, implement, and validate data mapping, transformation, and integration solutions for payment integrity. Investigate and resolve complex data quality issues, create mapping specs and documentation, partner with stakeholders, and mentor analysts to improve data quality and automation.

Analyze large healthcare datasets to extract insights, build data models, reports and dashboards, ensure data quality, collaborate with cross-functional teams, and present findings to stakeholders.

Supports a large-scale government data migration from planning through conversion and validation. Analyzes source and target systems, develops conversion scripts, supports API integration, defines data mappings and transformations, and produces stakeholder-ready documentation. Provides recommendations on migration approach and data quality, collaborates with technical and business teams, and validates migrated data for completeness and accuracy. The role is remote within the United States and requires Public Trust or MBI suitability eligibility.

Own end-to-end analytics for the Pro product: build production data pipelines and dbt models, define north-star metrics, design dashboards and full-funnel reporting, lead A/B experimentation and causal inference, embed AI tooling, and deliver clear data-driven recommendations to product and leadership.

Manage daily Data team operations, research and analyze datasets, build internal and external reports (including an annual Startup Ecosystem Ranking), and maintain/improve Python scripts and data infrastructure to deliver actionable insights.

Audit and reconcile marketing and lead data end-to-end, maintain campaign tracking and platform integrations, troubleshoot data flow issues, manipulate large datasets to identify discrepancies, coordinate with vendors and stakeholders, and recommend process improvements to ensure accurate marketing-to-intake reporting.