Top Data Analyst Jobs in Denver & Boulder, CO

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.

Develop business intelligence and revenue reporting tools, automate Finance reporting processes, perform ad hoc and quantitative analyses, and translate complex data into actionable insights. The analyst will support company initiatives, present findings to technical and non-technical stakeholders, and provide decision-making guidance across the organization.

Analyzes wholesale voice, IP transit, peering, and CDN pricing, margins, traffic, financial performance, and deal structures. Builds pricing, forecasting, capacity, COGS, and what-if models; loads rate sheets; produces management reporting; monitors customer trends; resolves invoice disputes; and partners with Finance and Sales on pricing decisions and margin optimization.

Develops and maintains Power BI dashboards and data models, defines KPIs with stakeholders, validates data accuracy, and collaborates with Data Engineering on optimized analytical models. The role documents data lineage and reporting assumptions, supports self-service BI through communications and training, and automates manual reporting processes. It requires SQL, Power BI, DAX, Power Query, data modeling, and data warehouse knowledge, plus strong communication and cross-functional collaboration skills.

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.

Analyze clinical data completeness, reliability, and effectiveness across healthcare facilities, vendors, interoperability networks, and integration pathways. Reconcile claims with clinical records, identify missingness and latency, report ADT coverage, evaluate data technologies, recommend vendor configurations, and prioritize facilities for direct acquisition. Partner with product, engineering, and clinical teams to improve scalable, trustworthy data pipelines and support TEFCA and QHIN strategy.

Analyze workforce and human capital data for federal HR and workforce modernization projects. Develop dashboards, visualizations, benchmarking studies, executive briefings, analytical presentations, and reports using Excel, PowerPoint, Power BI, Tableau, or equivalent tools. Translate complex findings into clear recommendations for senior leadership and support projects requiring government security clearance eligibility and U.S. citizenship.

Leads complex cross-functional analytics projects from scoping through delivery, producing executive insights and recommendations. Builds reusable datasets, semantic models, and certified Power BI assets; automates reporting and data preparation; partners with business, engineering, and governance teams to improve data quality; and mentors analysts. The role requires advanced SQL, Power BI, DAX, Python, and cloud data platform expertise, plus insurance industry experience and strong stakeholder communication.

Leads complex qualitative and quantitative public health analyses and evaluation activities. Develops, integrates, cleans, validates, and analyzes multi-source datasets, including CDC and national-level data. Performs mixed-methods analysis, implementation-measure evaluation, data-quality assurance, cross-site comparisons, and reproducible analytic process development. Produces technical documentation, reports, briefings, recommendations, and guidance for program improvement while supporting government evaluation and performance-measurement requirements.

Analyze and tune sanctions, fraud, and AML models; evaluate performance, reduce false positives, develop features and datasets, automate analysis, troubleshoot data issues, and communicate findings to technical, compliance, regulatory, and senior management stakeholders.

Analyze cybersecurity and continuous-diagnostics data to identify vulnerabilities, control gaps, asset issues, and risk trends. Validate and normalize data, reconcile asset and vulnerability records, develop dashboards and reports, and provide remediation recommendations. Coordinate with system owners and security teams to resolve discrepancies and verify remediation. Document analytical methods, data definitions, assumptions, and results.

Analyze raw usage, identity, license, and cost data from cloud, SaaS, and observability sources. Profile and map data to canonical schemas, design transformation and cost-allocation logic, assess application attribution, derive business taxonomies, and reconcile observed usage with vendor invoices. Contribute to FOCUS alignment, attribution precedence, shared-endpoint allocation, coverage reporting, and data quality specifications for engineering implementation.

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.

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.

Performs data quality assurance for large datasets by validating imports, updates, transformations, and extracts. Writes SQL test queries, reviews database logic, executes test cases, identifies defects, verifies corrections, and documents testing results. Collaborates with data engineers, business analysts, project managers, and QA professionals to ensure data integrity and compliance with requirements.

Lead supply chain analytics and AI initiatives focused on MRP accuracy, inventory optimization, production scheduling, and process improvement. Develop statistical, machine learning, generative AI, and reporting solutions; manage supply chain metrics and data governance; optimize SAP MRP parameters; support SIOP planning; and partner with procurement, manufacturing, engineering, and IT teams. Mentor analysts and data scientists while driving automation, analytics strategy, and measurable operational improvements.

Build risk data models, analyze fraud and risk trends, create Tableau dashboards and automated reports, and deliver actionable insights to Risk Operations leaders. The role manages analytics requirements and roadmaps while using SQL, dbt, Dataform, and AI tools to support fraud strategy, compliance monitoring, loss forecasting, and executive reporting.

Administer and improve Workday and multi-platform HR security, including role-based access, security groups, access reviews, request approvals, audit support, governance documentation, and compliance controls. Evaluate elevated access requests, identify risks, resolve routine issues, coordinate remediation, and escalate complex decisions. Partner with HR, IT, Legal, and Compliance stakeholders to strengthen policies, processes, and least-privilege access across Workday, Peakon, UKG, Prism, and HR data platforms.

Senior individual-contributor analyst leading end-to-end, high-stakes analyses, designing dashboards and reporting, mentoring analysts, applying statistical methods and causal inference, partnering with analytics engineering to shape warehouse models, and translating findings for technical and non-technical stakeholders.

Collects and analyzes performance data, identifies trends, evaluates program effectiveness, and develops reports and visualizations for stakeholders. The role standardizes datasets, improves data collection and analytical methods, and supports data-driven decisions. It requires statistical analysis, data manipulation, visualization, and familiarity with machine learning and predictive analytics. The position is contingent on contract award and requires the ability to obtain and maintain an active Secret Clearance.

Analyzes complex sustainability datasets, validates calculations and metrics through QA and UAT, maintains assessment files and customer data exports, investigates data issues using SQL, and collaborates with product, engineering, and customer-facing teams. The role also supports automation, documentation, sustainability research, and reliable environmental impact reporting.

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.

Analyze and manipulate large datasets supporting energy modeling and SEM programs. Review data before and after modeling, maintain standardized templates and databases, integrate data into statistical software, quality-control models and reports, and create work instructions. The role also involves automating data processing, troubleshooting Visual Basic and Excel tools, managing Smartsheet data, supporting benchmarking reports, and collaborating with internal teams and occasional clients.

Own and maintain the data catalog, vendor and licensing records, dataset lineage, field definitions, and calculation documentation. Write SQL to trace, join, reconcile, and validate data; investigate discrepancies; QA derived metrics; prepare data extracts; and troubleshoot issues with engineering, offshore data teams, PMO, and customer service. Use AI tools to accelerate data work and maintain clear documentation for technical and non-technical stakeholders.

Leads stop loss claims data coordination for primary clients, identifies claimants, prepares claim-entry data, builds dashboards, presents insights to leadership, and drives continuous improvement initiatives. Requires at least three years of claims data analysis or operations experience, specific stop loss claims expertise, and a bachelor’s degree in Business or Analytics or comparable experience.