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 North American customer research agenda: design and run tracking and ad-hoc studies, analyze quantitative and qualitative data, translate findings into actionable commercial insight, present to stakeholders, manage and coach direct report, and improve research processes and methodologies.

Lead KPI reporting, funnel analysis, forecasting, and business diagnostics for Enterprise Growth across Coursera + Udemy. Build unified definitions and durable self-serve reports, support experiments and inside-sales/outsourced partner evaluation, and provide analytical inputs for target setting and prioritization to drive growth and conversion improvements.

Lead the Data Platform Engineering team owning ETL/reverse-ETL pipelines, replication, and production datastores. Define architecture, roadmap, standards (IaC, observability, schema contracts), mentor engineers, drive incident response and durable fixes, and partner on cross-team technical decisions and operational reliability for data correctness, completeness, and timeliness.

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.

The Senior Business Systems Analyst will leverage ServiceNow for automation, aligning solutions with business needs, enhancing user experience and driving AI-assisted solutions.

Lead and build a product analytics function: define KPI framework, instrumentation, and self-serve analytics using Pendo and BI tools. Partner cross-functionally to measure product performance, surface insights, influence roadmap and embed AI-powered analytics into product lifecycle.

The Senior Data Engineer will design and implement scalable data models in BigQuery using dbt for analytics and reporting, ensuring data governance and optimal performance.

Lead design and operation of large-scale data pipelines and data APIs. Build Spark/PySpark workflows on Databricks, optimize job performance, manage data quality and observability, and develop MCP servers and AI-agent integrations. Mentor engineers, define standards, support production incidents and on-call rotations, and collaborate with stakeholders to deliver scalable data platform products.

Lead architecture and buildout of a new graph-backed enterprise data platform: design ingestion, graph and relational storage, entity resolution pipelines, temporal models, ETL/ELT pipelines, governance, APIs, and production connectors. Ship scalable graph data models, traversal queries, and platform roadmap while enabling observability, security, and containerized deployments.