Top Data & Analytics Jobs in CO

Supports data analysis, monitoring, and automation projects within AI Operations. Analyzes operational data, prepares datasets, identifies improvement opportunities, assists with automation that reduces manual monitoring, documents practices, gathers requirements, shares findings, and communicates technical work to nontechnical audiences.

Leads People Analytics enablement and BI strategy, overseeing semantic models, certified data products, metric governance, data foundations, advanced analytics enablement, demand prioritization, and adoption. Partners with People Analytics, IT, and HR Strategy teams to create trusted workforce data, reusable semantic assets, and decision-ready insights. Manages teams and operating models while driving data quality, governance, certification, self-service analytics, AI access, and scalable insight delivery across the enterprise.

Performs data profiling, quality analysis, governance, metadata and lineage management, and Master Data Management support. Collaborates with data owners, stewards, business stakeholders, and technical teams to resolve issues and improve governance processes. Maintains glossaries, dictionaries, controls, metrics, and reports; supports enterprise data initiatives, communications, training, and stakeholder adoption. Provides guidance to less experienced analysts while applying governance standards and documenting business requirements.

Owns PMO metrics, dashboards, and reporting infrastructure for aerospace programs. Develops Power BI dashboards, integrates data from multiple systems, standardizes KPIs, produces program reports, performs root-cause and trend analysis, and supports risk mitigation. Establishes data governance, tracks vendor performance, and serves as a liaison across engineering, manufacturing, quality, finance, and operations. Promotes self-service analytics and data-informed decision-making across the organization.

Build and own scalable data platforms and ingestion pipelines using BigQuery, dbt, and modern ingestion tools. Design batch and CDC workflows, improve reliability and observability, implement governance and access controls, and support analytics and AI agents. Develop Python services and internal tooling, contribute to architecture and lakehouse experiments, collaborate with stakeholders, and mentor engineers. The role requires strong SQL, Python, cloud infrastructure, testing, CI/CD, and AI-assisted development experience.

Develop and enhance data analytics solutions for Internal Audit, including automated testing, continuous monitoring, dashboards, reporting, risk analysis, and anomaly detection. Partner with audit teams, data owners, and stakeholders to analyze complex data, document procedures and findings, improve audit processes, and evaluate responsible applications of AI, machine learning, and automation.

Own Toast’s Voice of the Customer program across customer segments, analyzing NPS, CSAT, CES, qualitative feedback, and business metrics. Identify root causes of customer pain, develop data-driven recommendations, improve CX measurement practices, and influence cross-functional teams to prioritize customer-focused solutions. The role also builds listening channels, promotes customer-centric decision-making, and aligns CX priorities with organizational goals.

Analyzes customer behavior, marketing performance, and business trends to deliver actionable insights. Builds predictive models, forecasts, dashboards, data pipelines, and self-service analytics solutions. Designs experiments, performs statistical and hypothesis testing, evaluates attribution and customer metrics, and communicates findings through concise presentations to stakeholders and leadership. Collaborates across marketing, partnerships, finance, sales, product, engineering, and machine learning teams to support strategic decision-making.

Build Deepgram’s governed decision layer above warehouse gold tables. Responsibilities include modeling cross-system entities, owning semantic and metrics definitions, creating agent-facing data tools and MCP surfaces, implementing data quality assertions and reconciliation checks, evaluating AI agent accuracy, and answering business questions while leaving reusable models behind. The role requires production-grade SQL and Python, semantic-layer ownership, strong data modeling judgment, AI-native workflows, clear writing, and comfort building infrastructure from scratch.

Lead analytical investigations and build measurement frameworks, dashboards, reporting, and reusable data products for Customer Experience leadership. Partner with data scientists on customer health scoring, forecasting, segmentation, and validation. Use SQL and Python to turn ambiguous business questions into decision-ready insights, document solutions, and operationalize analytics across CX teams.