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

Analyze large behavioral and transaction datasets, build reports and dashboards, collaborate with product and engineering to inform data-driven product decisions, automate analyses, communicate insights to stakeholders, and brainstorm new data uses to improve user experience.

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Reviews and analyzes large business datasets for accuracy, completeness, relevance, privacy, and quality. Conducts document reviews involving PII, identifies data issues and anomalies, provides feedback to support AI training, refines quality assurance standards, and communicates findings to project stakeholders while maintaining data privacy and security compliance.

Develops and maintains Power BI dashboards, reports, semantic models, KPIs, and visualizations using Microsoft Fabric and governed data. Performs data validation, reconciliation, requirements gathering, dashboard migration, documentation, user acceptance testing, training, and troubleshooting. Collaborates with analysts, engineers, governance teams, and government stakeholders to deliver analytics for education, workforce, financial, procurement, and operational reporting. Supports self-service analytics and evaluation of AI-enabled business intelligence capabilities.

Designs and maintains cloud data ingestion, ETL/ELT, transformation, integration, synchronization, and data quality processes in Microsoft Fabric. Builds Bronze, Silver, and Gold lakehouse layers; integrates enterprise systems and Ed-Fi REST APIs; performs data mapping, profiling, reconciliation, migration, and troubleshooting. Develops SQL, Python, and PySpark logic, documents pipelines, and collaborates with architects, analysts, governance teams, and source-system owners. Supports Ed-Fi migration planning and operational transition activities.

Owns performance measurement and analytics strategy across paid and organic media. Defines KPIs, designs testing and attribution approaches, interprets campaign data, and delivers recommendations that influence media and account-team decisions. The role establishes reporting standards, improves LOCALACT analytics capabilities, and partners cross-functionally with Paid Media, Organic, Account Services, and Marketing Technology to improve campaign performance and business-outcome tracking.

Provides remote administrative support for home care operations by managing correspondence, scheduling appointments and staff activities, preparing documents and spreadsheets, updating records, entering data, assisting clients and staff, tracking deadlines, and protecting confidential information. Requires strong organization, communication, computer, and recordkeeping skills, with familiarity in Microsoft Office or Google Workspace. Paid training and opportunities for advancement are provided.

Entry-level Data Analyst supporting Performance & Analytics for care operations. Build, validate, and QA recurring reports and dashboards (Retool/BI tools), pull and clean payer, clinical, and operational data, investigate discrepancies, maintain workflows and reporting-ready datasets, and support ad-hoc analytical priorities.

Collects, consolidates, cleans, analyzes, and visualizes experimental data from analytical equipment, test rigs, and pilot plants. Performs statistical analysis, anomaly detection, experimental design support, equipment validation, and QA/QC activities. Presents findings to technical leadership, identifies process improvements, and helps extract actionable insights from structured and spectral data.

Develop and support healthcare IT data strategies, governance frameworks, analytics roadmaps, data quality initiatives, metadata management, and enterprise data integration. Coordinate data migration, legacy clinical data integration, and clinical viewer transition efforts. Collaborate with stakeholders on analytics requirements, support dashboards and reporting, advise leadership on performance metrics, and ensure compliance with privacy, security, and governance requirements.

Entry-level data engineering development program involving three rotations, cloud-native data platforms, batch and real-time pipelines, distributed systems, ETL/ELT, data modeling, AI platforms, and enterprise data products. Participants use AWS, Spark, Java, Python, SQL, Snowflake, Kafka, and related technologies while gaining experience with LLM architectures, APIs, microservices, and secure production deployments.