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

Leads broadband business intelligence initiatives by analyzing complex datasets, developing cross-functional dashboards and reporting structures, guiding data strategy, and delivering customer and business performance insights. Presents advanced analyses and strategic recommendations to senior leadership. Requires expertise in SQL, ETL, data visualization, reporting design, and analytical modeling, with collaboration across technology, finance, marketing, telecom, supply chain, and procurement teams. This is a hybrid role requiring at least three days per week in the office.

Lead the architecture and development of Vercel’s next-generation data platform, supporting batch and real-time integrations, analytics, data warehousing, and AI/ML workloads. Design scalable systems using Kafka, ClickHouse, Tinybird, and Snowflake; establish data governance and security standards; guide architectural decisions and roadmaps; collaborate with engineering, product, security, compliance, and leadership teams; write production code; and mentor engineers.

Leads the enterprise data platform strategy, architecture, governance, and evolution. Manages a central data team and enables federated self-service analytics across business functions. Builds AI-ready data pipelines, RAG and Graph RAG architectures, custom data applications, observability, cost optimization, and AIOps capabilities. Requires hands-on expertise with Snowflake, dbt, modern ETL, Python, SQL, CI/CD, and Data Mesh architectures, along with 5+ years leading technical data teams.

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.

Leads analytics for Pricing and Supply, managing a team of approximately eight analysts. Partners with cross-functional leaders to prioritize analytical work, build dashboards and decision frameworks, improve metric quality, and generate insights into pricing, supplier coverage, marketplace performance, conversion, margin, and customer behavior. Coaches analysts, establishes scalable analytics processes, and collaborates with data engineering teams to improve data models, tooling, and self-service capabilities.

Own product analytics and customer success data domains by building governed models for product usage, feature adoption, customer health, onboarding, renewals, churn, expansion, and net revenue retention. Partner with Product, Customer Success, RevOps, Finance, and analysts to create semantic models, metric definitions, instrumentation, documentation, alerting, and self-service tools. Use dbt, Snowflake, Omni, Hex, and AI-assisted development to turn ambiguous stakeholder questions into durable data products.

Build and maintain Databricks-based data platforms, including ingestion, transformation, storage, governance, data modeling, and serving pipelines. Establish medallion architecture standards, canonical data models, quality controls, lineage, schema evolution, and reliable batch or incremental processing. Improve pipeline observability, scalability, idempotency, and recoverability while moving curated data to systems such as ClickHouse. Collaborate across application and analytics teams to create durable, governed production datasets.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

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.

Lead design and implementation of data architecture for healthcare systems, influence stakeholders, mentor teams, ensure regulatory compliance, enable data integration and transformation, and apply AI techniques to improve healthcare operations and reporting.

Own actuarial models and client-facing reporting measuring cost savings, outcomes, and performance of healthcare prior authorization programs. Analyze authorization and claims data, conduct impact evaluations, reconcile projected and realized results, investigate trends, and present executive-level insights to customers and leadership. Partner with clinical, customer success, data, and actuarial teams while maintaining reproducible, auditable methodology and documentation.