Top Senior Data & Analytics Jobs in Denver & Boulder, CO

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

Lead Retail GTM analytics and territory operations: build reporting, automate workflows, design territory models, manage data quality/enrichment, and deliver decision-support tools across Salesforce, Snowflake, and Sigma to scale sales coverage and drive growth.

The Senior Analytics Engineer will design and implement scalable data solutions for Finance Analytics, reconcile data accuracy, and collaborate across teams to enhance financial datasets and reporting workflows.

Lead North American customer research agenda: design and run tracking and ad-hoc studies, analyze quantitative and qualitative data, translate findings into actionable commercial insight, present to stakeholders, manage and coach direct report, and improve research processes and methodologies.

Lead automation and measurement of the AI Governance program by building self-service dashboards, tracking Time-to-Approval and throughput, analyzing trends to remove bottlenecks, producing C-suite Evidence Packs, recommending workflow improvements, and collaborating with delivery analysts to increase governance maturity and operational throughput.

Lead retention and loyalty strategy for Sling and DISH video services using advanced analytics. Build financial models, identify churn risk, design and execute cross-functional initiatives, support AI/ML-driven solutions, and present insights to senior leadership to improve customer lifetime value and profitability.

The role involves operational support for data warehouse systems, optimizing pipelines on AWS, managing CI/CD processes, and collaborating on data transformations.

Lead the design and operation of automated compliance monitoring for consumer lending: translate regulations into rule-based data checks, own exam and audit data requests, triage exceptions, drive automation, steward compliance data, and provide technical mentorship to a supporting analyst. Produce audit-ready, reproducible evidence for regulators, bank partners, auditors, and senior leadership.

Build and operate an enterprise Databricks lakehouse: design and maintain Bronze and Silver ingestion/transformation pipelines (batch/stream/CDC), implement Unity Catalog and secure platform constructs, create CI/CD for data assets, enforce data classification and quality, and collaborate with domain teams to enable governed data for analytics.

Own and design the Databricks Gold and enterprise semantic layer: implement governed facts, dimensions, KPIs, and semantic models. Translate business KPI definitions into auditable transformation logic, enforce governance promotion paths, review models for correctness, coach domain teams, and ensure traceability, documentation, and compliance-aware data exposures for BI and self-service analytics.

Lead KPI reporting, funnel analysis, forecasting, and business diagnostics for Enterprise Growth across Coursera + Udemy. Build unified definitions and durable self-serve reports, support experiments and inside-sales/outsourced partner evaluation, and provide analytical inputs for target setting and prioritization to drive growth and conversion improvements.

Design, build, and maintain scalable dimensional data models, semantic layer, and production transformation pipelines. Collaborate with Data Engineering, Data Science, BI, DevOps, and Product to enable AI-ready data, ensure data quality and governance, support ML feature delivery, and coach analytics team members for robust, production-ready data products.

Lead and grow a data engineering team that builds and operates ingestion, transformation, orchestration, and serving layers and a self-serve analytics substrate. Own data quality, observability, cost efficiency, SLAs, and engineering practices while partnering with Data Science, BIE, Analytics, and Product to deliver reliable, reusable data products.