Top Entry Level Data & Analytics Jobs in Denver & Boulder, CO

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.

Coordinates research and analytics initiatives supporting economic development, neighborhood planning, and downtown engagement. Responsibilities include maintaining databases, dashboards, and development maps; analyzing market, transactional, survey, and travel behavior data; supporting reporting and communications; engaging stakeholders; assisting with events; and providing administrative and cross-team support. The role requires strong data management, analytical, organizational, communication, and quality-control skills, along with proficiency in Excel and related GIS, CRM, and visualization tools.

Experiential learning program introducing students to market research and analytics. Participants receive scholarships, technical training, mentorship, professional development, and experience using consumer data to solve real-world business challenges. They will translate data into actionable client insights and present a final case study. The program is intended for juniors graduating between 2027 and 2029 who are interested in insights, data analytics, paid media, market research, CPG, or retail.

The BI Analyst develops dashboards, reports, and visualizations; gathers business requirements; performs ETL and SQL-based data analysis; ensures data quality and governance; identifies trends and anomalies; provides recommendations; and trains users on BI tools and reports.

Coordinates freight weight-related research and analysis in a fast-paced transportation environment. The role requires analytical ability, computer proficiency, self-management, willingness to learn, and preferably experience with less-than-truckload transportation. This is a full-time Monday-through-Friday position with various shifts and includes comprehensive benefits.

Own the data and technology strategy for business intelligence, lead complex metric frameworks, define reporting metrics layers, and enable self-service analytics. Serve as the technical SME for BI tools and frameworks, mentor team members, partner with business leaders on OKRs, and transform tactical reporting into data and insights supporting predictive modeling and strategic consulting.

Build and maintain scalable data pipelines, infrastructure, data models, and APIs using Python, SQL, Airflow, Snowflake, dbt, Terraform, and cloud services. Ensure data quality, security, observability, and reliability while collaborating with analysts, product managers, and engineering teams. Own aspects of the FastAPI data service, including design, deployment, monitoring, and performance. Handle sensitive healthcare data in compliance with governance standards.

Leads a data engineering team and supervises one Data Engineer while designing, maintaining, and optimizing reliable data pipelines and infrastructure. The role integrates internal and external data sources, supports SaaS analytics dashboards and connected platforms, improves data-store performance, and ensures infrastructure quality, security, and uptime. Requires proficiency in Python, databases, distributed processing, orchestration, AWS, and machine learning.

Conducts research and outreach to collect official local election documents, processes election and candidate data, and maintains Ballotpedia’s database. Monitors election schedules, audits and cleans data, interprets election materials, researches election laws, and improves workflows and local election coverage. The role requires careful, organized, neutral research, collaboration, concise communication, and effective use of online productivity tools in a fully remote environment.

Leads hands-on big data processing, data engineering, and analytics workflows using Azure Databricks, Python, and SQL. Develops insights and reporting with Power BI, Tableau, and Excel. Analyzes complex datasets, communicates findings to business stakeholders, manages competing priorities, meets deadlines, and promotes continuous improvement.