Top Data Analyst Jobs in Denver & Boulder, CO

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.

Lead data analysis and reporting for the Trading team, build and maintain dashboards and governed analytics, deliver quantitative research, mentor juniors, and present insights to stakeholders to support decision-making and next-gen trading platform development.

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

Own and maintain the Propel PLM system to ensure accurate product data, BOMs, and integrations with ERP/CRM. Configure workflows, roles, and data structures; validate product and manufacturing documentation; support cross-functional teams; lead PLM projects; drive data quality improvements, user training, and continuous system enhancements to align PLM with production and supply chain operations.

Analyze transactional and operational payments data to monitor performance, detect risk and fraud, and improve collections. Build, validate, and automate daily/weekly/monthly reports and alerts, consolidate data sources, deliver insights to stakeholders, and support special analytics projects to drive operational efficiency.

Perform advanced analysis of large datasets to optimize field efficiency and logistics, build forecasting and headcount models, create Tableau dashboards, lead cross-functional alignment, use predictive analytics/AI to automate reporting, and present data-driven recommendations to operations leadership.

Lead Data Analyst responsible for advanced analytics, real-time dashboards, capacity modeling, and network performance insights. Collaborates with stakeholders to identify inefficiencies, run tests and pilots, and deliver actionable recommendations to improve service provider performance and network operations.

The Data Analyst in Revenue Operations will analyze sales data, build models, and create reports using SQL, Excel, and BI tools to empower business decisions.

Serve as a Senior Data Analytics Consultant specializing in Dynatrace and observability to analyze digital experience data, produce dashboards and reports, advise 4–8 enterprise clients, present findings to technical and executive audiences, configure tooling, influence product roadmap, and support client enablement and account growth.

The Lead GTM Data Operations Analyst will operate and extend AI-driven data quality pipelines, optimize agent outputs, and monitor offshore resolution teams, ultimately improving data accuracy and management in a dynamic, evolving environment.

The Senior Data Analyst will perform hands-on analytical work using SQL, design A/B tests, develop dashboards, and partner cross-functionally to drive data-informed decision-making across various teams.

The Data Strategy & Sourcing Analyst transforms product data into a strategic asset, ensuring data integrity and driving cost savings through sourcing. Responsibilities include establishing a Single Source of Truth, conducting data analysis, and collaborating with teams for financial impact. The role requires strong analytical skills, proficiency in SQL, and experience with data management tools.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Clean, transform, process, and query programmatic datasets to support educational programs. Ensure data integrity through testing, auditing, and documentation. Build dashboards, automate workflows, identify operational bottlenecks, and provide cross-functional analytical support. Participate in annual student application evaluations and collaborate with program, data, and engineering teams to drive data-driven operational improvements.

Analyze customer implementation and product usage to identify drivers of adoption, retention, and expansion. Build dashboards, quantify configuration and workflow impacts, surface deployment friction, and partner with Product, Sales, and Customer Success to create evidence-based playbooks and metrics that inform roadmap and go-to-market strategies.

Design, develop, and maintain Power BI dashboards and reports in a classified DAF SIPR environment. Build data models, perform ETL with Power Query, write and optimize DAX, ensure data quality/security, collaborate with stakeholders and data engineers, and provide ongoing support and governance for enterprise-scale Power BI solutions.

Own RevOps data models and BI infrastructure to drive GTM strategy. Clean and analyze datasets, build predictive models, define and track leading/lagging KPIs, deploy dashboards, document data definitions, and deliver executive-ready insights while partnering cross-functionally with Finance and GTM teams.

Own and build the support reporting layer: ticket volume, SLA, resolution times, CSAT/CES/sentiment, and capacity. Produce dashboards and analyses for leadership and engineering, maintain data quality and governance, prioritize issues using multi-signal models, and surface Voice of Customer trends to close the loop with Product and GTM.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Analyze, integrate, clean, and model operational and technical data to produce dashboards, reports, and forecasts. Identify trends, lifecycle/status, risks, and noncompliant assets; support automation, data quality improvements, and decision-making across engineering and operations teams.

Lead analytics work across revenue, product, customer, and operations by building dashboards, conducting deep-dive analyses, defining metrics and reporting standards, validating data quality with Data Engineering, and using AI tools to automate reporting and accelerate insights. Communicate findings to technical and non-technical stakeholders and proactively surface trends and opportunities.

Own and govern supply chain master data (items, BOMs, vendors, costs, units, MRP settings). Define standards, run audits, support ERP/ planning system configuration and enhancements, train users, and support cross-functional teams on data setup and lifecycle changes.

Lead product analytics: build and maintain dbt models and Looker dashboards, define KPIs, analyze funnel and user journeys, design and evaluate A/B tests, size roadmap impact, and deliver partner and ad-hoc insights to inform product and executive decisions.

Design and implement BI solutions: build data models, automations, ETL/ELT workflows, dashboards, and ad-hoc analyses. Monitor and analyze RF/video performance using Dataminer/Qligent or similar tools. Collaborate with cross-functional teams, document requirements, and deliver actionable insights to optimize hybrid terrestrial and satellite video delivery.

The role involves building and scaling a Closed-Loop Design Program that enhances pre-sales engineering through data science and analytics in supply chain automation.