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

Build and maintain Tableau dashboards, define KPIs, validate data, and query large datasets with SQL. Analyze cross-channel marketing performance across paid media, CRM, ecommerce, web, and app channels. Translate findings into actionable business insights, recurring client reports, and executive-ready presentations. Collaborate with engineering, analytics, data engineering, and strategy teams while guiding stakeholders toward data-driven decisions.

As the founding engineer of the Data Intelligence team, you will design semantic layers, develop AI tooling, and automate data processes to drive business insights.

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

Lead independent validation and governance of credit and fraud models, build automated Python monitoring for model drift and performance, drive remediation with model developers, and liaise with audit and regulators to support Affirm Bank's model risk management.

Lead strategic vision and execution of GitLab's data platform and analytics capabilities, focusing on AI-enabled self-service analytics and data governance.

Design and maintain people analytics reporting, dashboards, and data models; perform advanced statistical analyses and survey design; automate workflows and collaborate with stakeholders to translate insights into actionable recommendations.

Lead design and scaling of the data platform and analytics pipelines. Build and maintain ETL/ELT workflows, integrations, serverless data services, and reliable data models. Mentor teammates, improve automation, observability, and data governance to support analytics and operational insights.

Embed with Revenue leadership to identify high-value questions, build scalable analyses, models, and visualizations, and use AI agents and LLM tooling to accelerate insight delivery. Advise data teams on models, metrics, and semantic layers; validate AI-assisted outputs; communicate recommendations to technical and executive audiences; and develop reusable tooling and documentation.

Architects and leads enterprise data engineering solutions, including data warehouses, master data management, data lakes, ETL pipelines, integration services, and data processing systems. Oversees end-to-end data solutions, troubleshoots complex engineering issues, ensures global data integration standards, and mentors developers, vendors, consultants, and partners. The role also supports data scientists and engineers through efficient database, warehousing, and data access architectures.

Leads teams designing and delivering enterprise-scale batch and real-time data engineering platforms. Defines data product roadmaps, architects Kafka-based event-driven systems, builds high-throughput pipelines, establishes streaming standards and governance, and develops interoperable, AI-ready data products. Oversees organizational data policies, architecture, integrity, storage, and information management while partnering with engineering, architecture, product, and banking stakeholders.

Develop and implement data solutions, pipelines, architectures, analytics, reports, and dashboards for clients. Apply Python, Java, ETL, business intelligence, and advanced analytics techniques to interpret complex data, improve operations, and support strategic decisions. Collaborate with stakeholders, manage client relationships, identify data challenges, and deliver high-quality managed services work while contributing to continuous process improvement.