Top Data & Analytics Jobs in CO

Leads a team of five experienced analysts and data scientists while personally owning strategic analytics across ecommerce, health, supply chain, inventory, fulfillment, and merchandising. Partners with executives, establishes KPI and reporting standards, prioritizes the analytics roadmap, and delivers actionable business insights. The role also advances AI-native, self-service analytics capabilities, strengthens data governance and quality, and builds a high-performing analytics culture.

Leads the technical direction and roadmap for MongoDB’s GTM analytics model portfolio. Translates sales and operations questions into scalable statistical and machine learning models, data pipelines, dashboards, experiments, and executive recommendations. Owns forecasting, segmentation, territory, account prioritization, and customer analytics programs; establishes model governance and measurement standards; partners with senior GTM stakeholders; and mentors analysts and data scientists.

Leads reporting and analytics initiatives, develops Power BI dashboards and KPI frameworks, performs trend and root-cause analysis, supports forecasting, and delivers actionable insights to business leaders. Partners cross-functionally to define requirements, improve data governance, validate reporting, and establish scalable standards. Mentors analysts and guides complex analytics workstreams while remaining hands-on with report development, SQL data extraction, documentation, and performance measurement.

Leads applied AI and health data architecture initiatives for payer clients. Designs cloud-native platforms, pipelines, data models, integrations, and modernization roadmaps across AWS, Azure, Databricks, and Snowflake. Oversees data quality, governance, anonymization, performance optimization, and legacy migrations while advising stakeholders on AI-ready architectures. Manages multi-team delivery, resolves technical issues, presents solution tradeoffs, and coaches practitioners.

Lead business intelligence for Customer Experience by building trusted data pipelines, models, governance practices, monitoring systems, and dashboards. Partner with CX leaders and technical teams to define metrics, investigate customer outcomes using advanced statistics, detect anomalies with AI, and improve data quality. Manage high-impact analytical projects independently, communicate findings to technical and non-technical audiences, establish AI-assisted analytics validation standards, and mentor data practitioners.

Build and maintain production data pipelines, dbt models, Airflow workflows, and governed datasets supporting People Analytics. Integrate Workday and other HR systems into reliable Snowflake data products, implement data quality monitoring, row-level security, semantic models, and AI agents. Partner with engineers, analysts, data scientists, and business stakeholders to deliver trusted data solutions, communicate technical trade-offs, enforce governance, and mentor other engineers.

Build and maintain production data pipelines, curated datasets, dashboards, automation, and event-based data structures using Databricks and Airflow. Ensure data quality, reliability, governance, testing, CI/CD, and anomaly detection. Partner with decision science and business intelligence teams on modeling and analytics initiatives, create self-service data patterns, integrate AI-assisted tooling, modernize data services, lead complex projects, and mentor associate engineers.

Own the people analytics roadmap, build reliable HR data pipelines and reporting, and deliver workforce, talent, and process insights. Analyze employee lifecycle operations, measure performance, identify automation opportunities, and develop dashboards and predictive analyses for senior leaders. Partner across People, HRIS, IT, Finance, Legal, and data teams to improve data governance, privacy, operational efficiency, and employee experience. Establish analytical standards and coach People colleagues on data-driven decision-making.

Leads and manages a business analyst team supporting a data platform. Partners with clients, product managers, engineers, and stakeholders to gather requirements, write user stories, perform data gap analyses and source-to-target mapping, validate data using SQL, and support data quality, lineage, QA, Agile delivery, change management, and documentation. Requires healthcare data expertise, people leadership, strong communication, and experience translating technical information for varied audiences.

Develop and maintain customer-facing reports, dashboards, data models, and reusable datasets. Use advanced SQL to investigate customer questions, validate metrics, resolve discrepancies, and improve data quality. Partner with Customer Success, Product, Data Science, and Data Engineering to standardize reporting, support QBRs and value realization, and convert recurring analyses into scalable, automated data capabilities.