Top Senior Data Management Jobs in Denver & Boulder, CO

Administer and maintain CRM and data systems (EveryAction, Salesforce, BigQuery, CARTO), respond to staff and affiliate data/tech requests, ensure data quality and de-duplication, create and deliver training materials, build network capacity, manage vendor/consultant relationships, and travel occasionally for in-person trainings and support.

Lead analytics and reporting for DTC channels, develop dashboards and quality metrics, ensure data integrity, support vendor oversight, and drive performance improvements using data tools and quality processes focused on Medicare sales.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

Lead a small data engineering team partnering with Engagement Marketing to build scalable ETL/ELT pipelines, ensure data quality, define marketing metrics, integrate trusted data with ad platforms, and drive the data roadmap to enable measurement and growth.

Lead a team delivering actuarial statistical reporting, regulatory submissions, and analytics. Ensure compliance with bureau requirements, drive automated reporting and UAT for policy/claims systems (Guidewire, Solartis), partner with actuarial, technology, and vendors, and manage stakeholder/regulator interactions while mentoring staff and improving data governance and reporting processes.

Lead and mentor a data engineering team to design, build, and maintain scalable data platforms, pipelines, and warehouses. Ensure data quality, governance, security, and performance; collaborate with data science and BI teams; manage projects, budgets, KPIs, and technology selections; drive automation and DataOps/DevOps practices to enable data-driven decisions across the enterprise.

Lead a Salesforce data engineering team to design, deliver, and support Salesforce-to-Salesforce integrations and migrations, data modeling, ETL/transformations, automation, and observability. Manage hiring, performance, and career development; partner with stakeholders; adopt AI/LLM agent tooling to automate workflows and improve data quality; reduce technical debt and document systems and processes.

Lead a hands-on data engineering team to build and scale production data pipelines, datasets, and observability for alternative-data products. Drive architecture, data modeling, QA, and AI-ready dataset design while coaching engineers, partnering with product and research, and owning operational excellence across Databricks, Airflow, SQL, and PySpark.

Manage CVS Health's data partnerships and monetization strategy, source new partnerships, ensure operational success, and drive data product adoption across analytics teams.

Serve as the analytics bridge between marketing/operations and data teams: translate business questions and KPIs into clear product requirements, own delivery of treated tables, semantic layers, reports and dashboards, align stakeholders on a single source of truth, run gap analyses, document processes, and ensure delivered data products drive decision-making and adoption.

Lead enterprise data strategy and governance, build AI-ready data infrastructure and BI systems, own SharePoint platform, partner cross-functionally to ensure data quality, access, compliance, and user adoption.

Manage day-to-day execution of regional assessment builds and readiness operations in Renaissance (Illuminate) DnA, maintain data quality and compliance, coordinate vendor data collection, develop documentation and training, support regional stakeholders, and continuously improve assessment and data workflows to ensure timely, accurate reporting.

Lead and develop a team delivering enterprise data engineering, analytics, and governance. Oversee data pipelines, ETL/ELT, cloud platforms, integration services, and stakeholder engagement to enable data-informed decision-making across the university system.

Analyze medical claims (inpatient, outpatient, SNF, rehab, professional, DME) to identify utilization and root causes. Pull/integrate data, perform QA, present findings, maintain attribution methodology, coordinate stakeholders, and develop tools. Primary coding: Hive, SQL, Python.

Lead a team of ~7 data scientists to deliver timely, accurate product analytics and experimentation insights; manage people, mentor staff, partner with product and engineering, and build accessible data products and measurement practices.

Lead end-to-end delivery of data platform engagements: design and implement scalable ingestion and transformation pipelines, write and review production code (Python/SQL/Scala/Spark), architect cloud environments, advise clients, manage and mentor teams, and support practice development and business development activities.

The Data Manager oversees the full lifecycle of critical data, ensuring high-quality integration and analytics. Responsibilities include data operations, assessment of sources, collaboration with developers, and support for rapid-prototype phases.

Lead a team of data engineers and analysts, define the data engineering roadmap, oversee data infrastructure, ensure analytics delivery, and establish data governance standards.

Manage client-facing data and analytics projects: define data strategy, build automation and ETL, develop visualizations and predictive analytics, drive transformation, manage scope/budget, and communicate findings to non-technical stakeholders while leveraging finance knowledge.

Manage and grow a data engineering team, overseeing the design and maintenance of data platforms using Snowflake, dbt, and Azure. Drive best practices in data management and ensure reliable data movement and quality.