Top Data & Analytics Jobs in CO

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 enterprise-scale Akeneo PIM implementations, including solution architecture, platform configuration, data architecture, API development, and third-party integrations. Collaborate with developers, architects, clients, and stakeholders to deliver digital transformation projects. Ensure data privacy, security, and lifecycle protection while documenting technical solutions, gathering requirements, managing expectations, and mentoring junior team members.

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.

Build and optimize scalable batch and streaming data pipelines using Python, PySpark, SQL, and Apache Spark on AWS. Develop EMR data processing jobs, lead an Apache Airflow orchestration proof of concept, integrate Amazon Q for data quality and documentation, and implement GitLab CI/CD with infrastructure-as-code. The role emphasizes data governance, security, automation, performance, scalability, and cost efficiency while collaborating in Agile teams and presenting proof-of-concept findings.

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.

Lead enterprise data architecture across warehouses, data lakes, downstream applications, and AI workloads. Design data models, Medallion Architecture, ELT standards, semantic layers, APIs, access controls, and reusable datasets. Partner with business and BI teams to drive adoption, conduct architecture reviews, establish platform standards, and mentor data and analytics engineers. The role requires deep Snowflake, dbt, data modeling, pipeline, and semantic-layer expertise, with experience in AI data patterns and cloud infrastructure preferred.

Own and operate Toast’s enterprise data governance program, including data domain ownership, governance council coordination, policy compliance, business glossary management, metadata standards, catalog adoption, maturity assessments, and data literacy training. The role partners with business stakeholders, data stewards, catalog teams, and leadership to improve data trust, compliance, discoverability, and quality. It requires governance, metadata, SQL, data catalog, program management, and workshop facilitation experience.