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

Design and implement customer data solutions using Adobe Experience Platform and RTCDP. Configure XDM schemas, datasets, identities, and real-time profiles. Build ingestion pipelines, audience segmentation, and activation strategies. Ensure data quality, governance, and optimize platform performance while collaborating with marketing and technical teams.

Design, build, and operate scalable batch and streaming data pipelines, lakehouse and warehouse models, and data services. Own datasets end to end, improve Snowflake, Iceberg, Spark, and Flink performance and reliability, implement governance and observability, and support graph-serving data models. Partner with product and engineering teams, participate in on-call, review code and designs, and mentor junior engineers.

Manage client data, analytics, and AI managed-services workstreams. Develop data pipelines, dashboards, reporting, and analytics outputs; remediate data-quality issues; tune AI models and platform components; and improve data operations, observability, and reporting workflows. Collaborate with clients to translate business needs into data solutions, interpret insights, review deliverables, and mentor junior team members.

Leads a client-facing healthcare analytics team that designs and maintains prior authorization decision automation programs. Consults PaaS clients, develops strategic roadmaps, translates requirements into technical blueprints, analyzes authorization and claims data, and builds KPI reports using visualization tools. Manages direct reports, improves analytics processes and AI tooling, partners with product and engineering teams, and ensures automation outcomes and client KPIs are achieved.

Designs and maintains scalable data infrastructure, ETL/ELT pipelines, canonical datasets, and AI context layers. The role improves data quality and alignment across sales and finance systems, investigates data inconsistencies, leads requirements through UAT and implementation, supports analytics self-service, and partners with cross-functional teams to deliver process improvements and reliable business data.

Own data pipelines into and out of the warehouse, dbt models, data integrity, governance, identity resolution, reverse ETL, and quality monitoring across growth, lifecycle, and brokerage data. Partner with product, marketing, and operations teams to establish data contracts, ensure accurate and timely business metrics, and support regulated financial data requirements.

Lead the strategy and governance for GTM analytics across pre-sales, post-sales, solutions engineering, forward-deployed engineering, and professional services. Establish trusted source-of-truth metrics, data models, semantic layers, self-service analytics, and AI-assisted querying. Partner with Data, Finance, Sales, and Services leaders to resolve metric definitions, improve data access, consolidate reporting, and guide cross-functional programs without direct authority.

Build and optimize enterprise data warehouses, data lakes, and scalable batch and streaming pipelines. Support Snowflake and Databricks ecosystems, resolve ETL/ELT bottlenecks, automate workflows with Airflow and Control-M, and manage AWS-based infrastructure. Develop production-grade Python, SQL, and shell solutions while applying DevOps, CI/CD, IaC, and data modeling practices. Lead incident management, root cause analysis, operational metrics, and Agile collaboration with data and platform teams.

Staff Data Engineer responsible for setting technical direction, architecting scalable data platforms, leading cross-functional initiatives, improving reliability and performance, and enabling AI-assisted analytics and development. The role includes hands-on development with Python, SQL, cloud data warehouses, orchestration, infrastructure as code, Kubernetes, Kafka, and streaming pipelines, along with mentoring, technical advocacy, documentation, code reviews, and on-call troubleshooting.

Analyzes account portfolio whitespace, pipeline, deal performance, campaign attribution, rep productivity, budgets, forecasts, and expenses. Builds models and executive reporting to improve revenue planning, forecast accuracy, and account management decisions. Partners with Account Management, Finance, Marketing, Contract Administration, and regional leaders; validates Salesforce data and translates complex findings into actionable recommendations.