Top Data & Analytics Jobs in CO

Provides data analytics consulting for enterprise clients using Dynatrace observability, digital experience monitoring, and business analytics data. Manages client relationships, performs ad hoc analysis, creates reports and dashboards, presents findings to technical and executive audiences, configures tools, trains users, and influences product improvements. The role translates complex performance and engagement data into strategies that improve digital experiences and business outcomes.

Leads Toast’s analytics engineering function, owning enterprise data architecture, modeling strategy, analytics-layer development, and AI-ready semantic-layer vision. Builds and manages a team of analytics engineers, establishes roadmaps, partners with data engineering and business leaders, and drives scalable, governed data solutions across domains. Requires expertise in data modeling, dbt, SQL, stakeholder alignment, and people leadership.

Lead marketing analytics for customer upsell, lifecycle, activation, adoption, and retention initiatives. Analyze customer data and campaign performance, identify trends and growth opportunities, develop recommendations, and estimate business impact. Collaborate with Marketing, Sales, Finance, Analytics, and Web teams to improve customer experiences, attribution frameworks, dashboards, and self-service growth strategies.

Design and optimize ETL processes, data ingestion systems, streaming applications, and cloud data architectures using SQL, Python, Snowflake, AWS, and Redshift. Maintain and troubleshoot production data pipelines, integrate analytical outputs with business intelligence applications, optimize queries, and collaborate with analysts and engineers using Airflow and Databricks. Evaluate AI tools and emerging technologies to improve data warehouse workflows.

Creates, reviews, edits, and delivers 3D geospatial solutions from aerial and satellite imagery using proprietary software. Performs high-volume quality control, ensures compliance with product specifications, maintains consistency, reviews peer work, provides feedback, and prioritizes multiple tasks in a geospatial production environment. The role also requires mentoring or training experience and developing expertise in 3D product specifications and workflows.

Lead and grow a global data engineering team while establishing foundational data platforms and engineering standards. Design and oversee GCP-based pipelines, medallion data models, DataOps, monitoring, SLAs, CI/CD, governance, and data quality practices. Drive AI adoption across engineering workflows and build reliable, AI-ready data. Partner with business and technology stakeholders to prioritize roadmaps, deliver scalable solutions, and support data democratization.

Architects, deploys, and operates scalable data platform infrastructure supporting analytics. Responsibilities include administering Airflow and Superset, managing Terraform infrastructure, building CI/CD pipelines, enforcing security and compliance, developing DBT data models, cataloging assets in OpenMetadata, writing Python automation, and mentoring engineers. The role requires extensive infrastructure and data engineering experience across cloud platforms, containers, data security, and workflow orchestration.

Serve as the strategic analytics partner to GTM leadership, connecting Finance, Revenue Operations, Product, Growth, and sales leaders. Build trusted analytics infrastructure, define metrics and reporting, develop scenario models, and translate complex business decisions into executive recommendations. Own recurring business reviews and the end-to-end view of sales performance across routes to market, helping leaders evaluate product, pricing, compensation, organizational, and market changes.

Architects and leads enterprise data engineering solutions, including data warehouses, master data management, data lakes, ETL pipelines, integration services, and data processing systems. Oversees end-to-end data solutions, troubleshoots complex engineering issues, ensures global data integration standards, and mentors developers, vendors, consultants, and partners. The role also supports data scientists and engineers through efficient database, warehousing, and data access architectures.

Own implementation, maintenance, and optimization of client eligibility and claims data feeds. Analyze feed performance, troubleshoot discrepancies, produce error reports, test integrations with external partners, and improve internal tools, documentation, and processes to increase automation and reliability.

Leverage data analytics, business intelligence, and Python to deliver strategic insights and tailored solutions for clients. Build reports, dashboards, data pipelines, and support data architecture and quality initiatives. Analyze data from multiple sources to identify trends, improve operations, and inform decision-making. Collaborate with stakeholders and team members while continuously developing technical skills and contributing to process improvements.