Top Hybrid Senior Level Data & Analytics Jobs in CO

The Lead Data Analyst (Network) drives data-driven initiatives, dissects datasets, and provides actionable insights to enhance business performance and network efficiency.

Lead the development of data solutions using Palantir Foundry, guiding teams, solving complex problems, and ensuring operational excellence while fostering high performance and collaboration.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.

The Staff Data Platform Engineer will architect the data platform, define integration patterns, establish data governance, and mentor teams across the organization while ensuring data reliability and self-service capabilities.

As a Sr. Business Systems Analyst, you will enhance Salesforce and FinancialForce systems, manage business applications, and ensure SOX compliance while collaborating with cross-functional teams.

The Senior Portfolio Lead will oversee data management services for clients, ensuring quality deliverables, strategic oversight, and optimal clinical data flows, while leading cross-functional teams and managing complex client relationships.

The role involves assessing fraud program effectiveness, compliance with regulations, and providing strategic insights for risk management within the financial services industry.

The Senior Data Engineer will design and optimize large-scale batch and streaming data pipelines using Scala and Spark, oversee the data engineering lifecycle, and engage in technical discussions to improve system efficiency.

Leads a Data Science team at Gusto, focusing on product strategy using data and AI. Responsibilities include team management, developing measurement frameworks, supporting experiments, and influencing leadership decisions with insights.

Lead a team of decision scientists and business intelligence developers to deliver analytics solutions and drive business outcomes. Collaborate with stakeholders, establish automated processes, and maintain best practices in data analytics and visualization.