Top Data Analyst Jobs in Denver & Boulder, CO

Conducts data analysis, integrates multiple data sources, and creates forecasts, reports, dashboards, and ad hoc analyses. Defines data rules and quality requirements, audits reporting accuracy, identifies trends and operational opportunities, and communicates insights to stakeholders and management. Requires SQL and data reporting expertise, with preferred experience in procurement, supply chain analytics, ERP, BI tools, and sourcing platforms.

Build and maintain Engine X performance dashboards, reporting frameworks, data models, and complex SQL analyses using Snowflake. Track card, booking, rewards, spending, and retention metrics; investigate anomalies; support A/B tests; document metric definitions; and communicate findings to product, finance, and leadership. Collaborate with analytics and data engineering teams to validate pipelines and improve data quality.

Provides data analytics consulting for enterprise clients using Dynatrace observability, digital experience monitoring, and business analytics data. Manages client relationships, performs ad hoc analysis, creates reports and dashboards, presents findings to technical and executive audiences, configures tools, trains users, and influences product improvements. The role translates complex performance and engagement data into strategies that improve digital experiences and business outcomes.

Leads advanced analytics initiatives supporting Tribal healthcare programs and strategic decision-making. Develops predictive and prescriptive models, integrates complex data sources, establishes data quality frameworks, evaluates healthcare data resources, and produces reports and dashboards. Coordinates cross-functional projects, ensures federal compliance, supports quality measurement, mentors junior staff, and may serve as a team lead.

Develops Power BI dashboards, reports, queries, and ad-hoc analyses for supply chain operations and strategic decisions. Translates business needs and integrated data into actionable visualizations, enhances data integration and maturity, and identifies root causes through descriptive and prescriptive analytics. Collaborates with business, technology, analysts, and data scientists on agile product development, supports innovation, and helps junior team members succeed.

Analyzes data from internal and external sources to identify business performance trends, root causes, and improvement opportunities. Builds dashboards, visualizations, reports, and business intelligence tools for stakeholders in the fintech space. Partners with internal teams to define data needs, communicate findings, recommend operational improvements, and support the UX/UI experience of data products.

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 marketing measurement strategy through geo holdout and incrementality testing, forecasting, experimentation, and statistical analysis. Partners with Marketing, agencies, and Data Science to guide channel budgets and campaign decisions. Queries large-scale data using SQL and Python in Databricks and BigQuery, develops measurement models, automates analyses with AI tools, and mentors analysts while providing technical leadership.

Profiles and analyzes data sources, documents end-to-end lineage, maps source data to canonical models, and supports API schema design. Develops data quality, validation, metadata, and governance documentation while collaborating with engineers, architects, clients, and stakeholders to define clear technical requirements for enterprise data products, APIs, and analytics.

Analyzes and integrates complex datasets to produce actionable insights, reliable management reports, and data quality improvements. The role develops SQL-based analyses, monitors and configures systems, supports information systems projects, and communicates findings to technical and nontechnical stakeholders. Candidates must work independently, solve complex data challenges, and be proficient with Microsoft SQL Server, SQL Reporting Services, Excel, Access, databases, and a scripting language.

Design and optimize ETL processes, data ingestion systems, streaming applications, and cloud data architectures using SQL, Python, Snowflake, AWS, and Redshift. Maintain and troubleshoot production data pipelines, integrate analytical outputs with business intelligence applications, optimize queries, and collaborate with analysts and engineers using Airflow and Databricks. Evaluate AI tools and emerging technologies to improve data warehouse workflows.

Maintains and improves product, customer, supplier, and location master data across enterprise systems. Responsibilities include data creation, cleansing, auditing, discrepancy resolution, governance compliance, NPI readiness, cross-functional workflow coordination, system integration support, reporting, user training, and process improvement. The role partners with PMO, IT, Finance, Sales, Marketing, and Supply Chain teams in a hybrid CPG environment.

Manages technology governance, risk, and compliance activities, including vendor risk assessments, policy governance, audit coordination, access reviews, security-awareness training, and regulatory compliance. Uses ServiceNow and related platforms to document assessments, audits, policies, permissions, and third-party requests. Advises stakeholders on controls, responds to audit findings, supports role-based access initiatives, and serves as a GRC subject-matter expert across city agencies.

Analyze production drive-thru voice AI data, build SQL reports and dashboards, monitor KPIs, identify conversation error patterns, and improve NLU models, conversation flows, and LLM behavior through machine learning and rule-based techniques.

Deliver recurring and ad hoc commercial analytics, client reporting, performance-guarantee calculations, dashboards, and value measurement. Define and govern metrics, validate data, improve documentation and workflows, and automate repeatable processes. Partner with Client Success, Commercial, Finance, Product, and Analytics teams to translate complex questions into actionable insights, client-ready narratives, and recommendations that strengthen client relationships and inform business strategy.

Analyze business performance, develop hypotheses, answer critical business questions, and build dashboards and reports in Sigma. Support budgeting, forecasting, data quality checks, and reconciliations while partnering with teams across growth, product, insurance, finance, and leadership. Serve as a trusted data advisor by answering metric and reporting questions and promoting data-driven decision-making.

Supports risk portfolio programs through strategic project planning, data analysis, dashboard development, process automation, vendor and ROI management, governance, and audit documentation. The role partners with risk analysts, data scientists, Product Management, Engineering, and other stakeholders to identify risk indicators, design controls, improve workflows with AI tools, and communicate actionable insights across credit, fraud, and reputational risk initiatives.

Analyze complex data to support company-wide decisions, building metrics, scalable data pipelines, dashboards, and reports. Partner with cross-functional teams and leaders to translate business needs into data problems, deliver actionable recommendations, and improve self-service reporting. The role also involves data storytelling, stakeholder training, and enabling data literacy. Preferred experience includes Spark, Python, statistical analysis, leadership reporting, software development practices, and AI tools.

Manage a team of 2–3 analysts while remaining hands-on with SQL, dbt models, dashboards, and complex operational analyses. Lead ambiguous, cross-functional initiatives, deliver recommendations to senior stakeholders, ensure data quality, and improve reporting automation. Partner on AI analytics strategy, data readiness, agent evaluation, and human-in-the-loop governance. Responsibilities include coaching, prioritization, performance management, technical review, KPI development, and operational insights across customer experience, fraud, payments, workforce management, and VIP functions.

Perform structured data conversion, cleansing, validation, and mapping for system implementations. Execute validation scripts, support UAT, document discrepancies, reconcile legacy and converted data, and escalate anomalies to senior consultants while maintaining organized records and templates.

Owns automated dashboards, SQL-based analysis, data pipeline monitoring, exploratory analysis, and executive recommendations. The role tracks marketplace KPIs such as customer lifetime value, acquisition costs, churn, and provider utilization while partnering with engineering and product teams on data requirements. It is fully remote within the United States and requires advanced SQL, dashboard development, and strong analytical communication.

Leads financial reporting, business intelligence, data modeling, and analytics support using Workday Financials and Adaptive Planning. Designs and configures reports, dashboards, data structures, and governance standards; troubleshoots applications and integrations; coordinates testing, documentation, training, and process improvements. Supervises staff and facilitates cross-functional finance working groups supporting budgeting, forecasting, sponsored awards, and financial analysis.

Analyze healthcare and clinical operations data to deliver actionable customer insights, physician performance reporting, care-quality dashboards, and scalable BI solutions. The role requires SQL-based data transformation, dashboard development, collaboration with clinical, product, engineering, and client-facing teams, and clear communication of findings. The analyst will also use AI tools for query generation, data cleaning, pattern recognition, and analytical summaries.

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.

Develops scalable data models, dashboards, reports, and analytical solutions that support business decisions. Partners with stakeholders to translate requirements, ensures data accuracy and usability, provides technical guidance to end users, documents architectures and processes, and communicates findings to technical and non-technical audiences. The role requires advanced Spotfire, SQL, and business intelligence experience, plus familiarity with modern data platforms and AI-assisted development tools.