Top Data Management Jobs in Denver & Boulder, CO

Lead managed data and analytics engagements to build modern data ecosystems, convert insights into strategic opportunities, manage client accounts, mentor teams, ensure delivery quality, manage risks, and drive cloud-scale development and growth.

Lead development and execution of data governance strategies, supervise and mentor teams, manage client accounts and deliverables, analyze data to inform business decisions, ensure compliance with firm standards, and identify improvements to data management processes.

Lead development and execution of data-driven strategies, manage and mentor a data analytics team, oversee project planning and delivery, analyze complex datasets to produce actionable insights, implement cloud data architectures, and support data governance and continuous improvement.

Lead development and implementation of data governance strategies, manage client accounts and deliverables, mentor and supervise teams, analyze data to drive business decisions, ensure compliance with firm methodologies and standards, and identify improvements in data management processes to enhance data-driven solutions.

Lead development and execution of data-driven strategies, manage projects and timelines, mentor and coach team members, analyze complex datasets to generate actionable insights, implement data governance and cloud data architectures, and ensure delivery quality and ethical standards.

Lead design and implementation of healthcare data architecture and pipelines, influence stakeholders, mentor teams, ensure compliance (HIPAA/PHI), apply interoperability standards, and drive data solutions and GenAI use cases to improve health system operations and reporting.

Lead data engineering engagements within managed services: design data architectures, build and maintain ETL pipelines, implement BI solutions, coach teams, engage stakeholders, and validate outcomes to optimize client performance.

Lead design and implementation of data architecture, models, ETL/ELT pipelines, and cloud data warehouses/lakes. Ensure data governance, security, and pipeline reliability while mentoring and managing a team and collaborating with stakeholders to translate business requirements into technical solutions.

Lead design and delivery of cloud-based data architecture, data models, ETL/ELT pipelines, data warehouses/lakes, and data security. Manage projects, mentor team members, ensure governance compliance, collaborate with stakeholders, and optimize cloud infrastructure for performance, cost, and scalability.

Lead data engineering projects to design and maintain ETL/ELT pipelines and architectures, leverage BI and cloud analytics (AWS/Redshift, S3, Glue), implement DataStage and CDC solutions, build reporting and visualizations (QlikView, Spotfire), manage and mentor teams, collaborate with stakeholders, ensure project delivery, performance tuning, and promote new technologies and process improvements.

Lead design and implementation of data architecture, build data pipelines and models, ensure governance and security compliance, manage large-scale projects, advise clients strategically, and coach high-performing teams to deliver data solutions.

Lead design and implementation of data architecture and cloud-based data engineering solutions. Manage large projects, translate stakeholder requirements into technical designs, ensure data governance and security, develop data models and pipelines, advise clients strategically, and coach teams to deliver operational excellence.

Lead and scale enterprise data governance operations: manage the data domain model and business glossary, run governance council operations, enforce data policies and compliance (SOC 2, GDPR/CCPA), drive catalog adoption and data literacy, and measure governance maturity and ROI through dashboards and remediation workflows.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

Lead a team evaluating new and existing data assets, standardize due-diligence and analytical methodologies, validate data quality and business value, partner with Product and Technology to support onboarding and OneTru cataloging, establish governance and lineage standards, and coach team members to drive data-driven product and revenue decisions.

The Senior Manager of Data Engineering will build a data platform, lead a team, and ensure data accessibility to support AI and business operations.

Lead Finance Data & Analytics to build trusted data sources, governance, and analytics for Finance and cross-functional stakeholders. Manage analysts, drive data strategy and Snowflake data models, produce insights via SQL and Tableau, and deploy AI solutions to optimize finance decision-making and operations.

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.

Manage Finance-focused data products, collaborating with teams to define requirements and drive delivery for financial analysis and reporting.

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.

The role involves driving product strategy for data infrastructure, leading cross-functional teams, and implementing MLOps practices for data engineering solutions.

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.