Top Hybrid Senior Level Data & Analytics Jobs in CO

Build user-facing data products by transforming internal data into actionable metrics. Collaborate with platform teams and data scientists to prototype, validate, and prioritize data sources. Write requirements and proposals, engage in user research, and deliver performant Python/SQL-based data features using Databricks and Postgres.

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 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.

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.

This role involves applying advanced data science and machine learning methods to healthcare data, leading teams, managing client relations, and developing analytics products for payers, while mentoring junior staff.

As an MDM Senior Architect-Manager at PwC, you will lead teams, manage client accounts, and architect end-to-end MDM solutions to enhance data management capabilities and align with business processes.

The MDM PIM Manager at PwC oversees Product Information Management solutions, ensuring data quality, mentoring teams, and driving innovation in product data practices.

Design, build, and optimize BigQuery-based data solutions and data models. Manage data storage, partitioning, clustering, ETL, and data quality. Collaborate with architects, data scientists, and engineers to deliver scalable, secure cloud data infrastructure and documentation; senior hires provide technical leadership, code review, and process improvement.

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.

Partner with People teams to turn HR and org data into actionable insights. Build complex queries, statistical analyses, dashboards, and a centralized people data repository. Drive data governance, data quality, and stakeholder communication to support hiring, retention, productivity, and workforce decision-making.

Serve as a Senior Data Analytics Consultant specializing in Dynatrace and observability to analyze digital experience data, produce dashboards and reports, advise 4–8 enterprise clients, present findings to technical and executive audiences, configure tooling, influence product roadmap, and support client enablement and account growth.

Lead design and execution of an enterprise data governance framework: set policies for data quality, metadata, lineage and privacy; run governance councils; operationalize data ownership and stewardship; implement data cataloging; embed controls in pipelines; ensure compliance and drive organization-wide adoption and change management.

Lead the enterprise data platform strategy and architecture, driving Snowflake/dbt-based platform evolution, self-service Data Mesh and medallion models. Build AI-ready pipelines, RAG systems, and observability/cost frameworks while managing a central data team, supporting federated BI, and executing hands-on technical work.

Lead and mentor a team of decision scientists to drive product strategy through analytics, experimentation, and measurement. Partner with product leads to prioritize initiatives, oversee end-to-end analytics projects, ensure statistical rigor in A/B testing, maintain event tracking quality, and deliver actionable insights using Databricks, Airflow, Python/R, Looker, and AI tooling.