Top Hybrid Senior Level Data & Analytics Jobs in CO

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.

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

Lead development and execution of data-driven strategies, manage project planning and delivery, mentor and coach team members, ensure quality and ethical standards, design cloud data architectures and governance frameworks, analyze complex datasets to produce actionable insights, and drive continuous improvement using advanced analytics and modern data technologies.

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

Develop and improve TransUnion's IP geolocation technology by analyzing large datasets, implementing automation algorithm improvements, and providing analytic insights. Collaborate with engineers and data scientists, use SQL/R/Python/MongoDB/BigQuery, and communicate findings to nontechnical stakeholders. Hybrid role with regular in-office work.

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 enterprise data modeling and architecture for the firm's lakehouse and Fabric platform. Define canonical data models, produce ERDs and dimensional schemas, govern Silver/Gold layers, run design reviews, document ADRs, and align data governance, lineage, security, and data contracts to ensure trusted analytics and self-service consumption.

As a Senior Data Engineer at Jellyfish, you'll build and maintain data pipelines, optimize orchestration, automate CI/CD processes, and enhance data integration while ensuring high performance and reliability.

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.

Design and maintain production data pipelines and infrastructure (Databricks, Airflow), ensure data quality and governance, build rollups and consumable datasets, implement CI/CD and automated testing, create and maintain Looker dashboards, mentor team members, collaborate cross-functionally, and integrate AI tooling to enable self-service analytics and data-driven product decisions.