Top Senior Data & Analytics Jobs in Denver & Boulder, CO

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.

Own BI analytics using a modern data stack to generate insights, build dashboards and self-serve tools, partner with stakeholders, and deploy AI-driven reporting and natural-language query solutions.

Lead a team of analysts and data scientists embedded in sales to build rigorous pilot analyses, create executive-ready business cases, expand consultative analytics across the partner lifecycle, and publish industry insights while coaching and scaling the Solutions Analytics function.

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 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 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.

Lead and scale cloud-based distributed data platforms and real-time data pipelines. Manage cross-functional on-site and offshore teams to deliver, troubleshoot, and optimize ingestion, curation, and streaming solutions. Improve AWS and data warehouse performance and cost, implement CI/CD for reliable deployments, and integrate AI-driven ops for anomaly detection and predictive data quality.

Lead and scale a casino analytics team to drive data-informed strategy, experimentation, and reporting. Partner with product, data science, and operations to deliver executive insights, build analytical frameworks, and develop high-performing analysts to unlock growth and operational efficiency.

Design and own end-to-end data models and dbt transformations on BigQuery, maintain the semantic layer in Lightdash, govern metrics, enable AI-assisted analytics workflows, partner with stakeholders to deliver trusted reporting, and lead data modeling standards, testing, and documentation.