Top Remote Entry Level Data & Analytics Jobs in CO

Develops complex analyses by integrating and standardizing disparate data sources, writing advanced SQL or SAS queries, creating data models and scoring methodologies, and presenting recommendations to business and analytics leaders. The role ensures data quality, documents scalable solutions, identifies process improvements, and supports strategic healthcare initiatives through advanced analytical tools and cross-functional collaboration.

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.

Designs, builds, and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, and SQL. Supports SQL Server, SSIS, SSRS, and data warehousing environments while improving performance, reliability, data quality, and scalability. Integrates enterprise data sources, enables reporting and AI/ML workloads, and partners with business and IT teams to deliver technical data solutions.

Designs, builds, and maintains scalable batch and streaming data pipelines and datasets in Databricks using Python, Spark, SQL, and Delta Lake. Supports SQL Server, SSIS, and SSRS environments while improving performance, reliability, data quality, and scalability. Integrates enterprise data sources, applies data warehousing practices, and partners with business users, analysts, and IT teams to deliver reporting, analytics, and AI/ML solutions.

Investigates data governance issues using information management tools and data sources, identifies root causes, and partners with data owners, clients, vendors, and architects on resolution. Establishes governance baselines, standards, metrics, audits, and reporting. Defines governance requirements for data elements, integrates governance tests into ETL processes, communicates governance benefits, and drives continuous improvement of data management systems, policies, and processes.

Supports healthcare data analytics and research projects by evaluating diverse datasets, developing statistical models, validating and cross-referencing data, analyzing care and outcome patterns, and communicating findings to nontechnical stakeholders and clients. The role includes learning healthcare data types, SAS programming, research design methods, and quality improvement analytics while collaborating across multiple teams and managing concurrent projects.

Lead and develop Analytics Engineers responsible for shared data foundations, platform capabilities, semantic models, developer tooling, and AI-enabled workflows. Define the team vision, operating model, roadmap, standards, and success measures. Partner cross-functionally to prioritize initiatives, improve adoption, guide architecture, and deliver scalable data assets and automation. Drive responsible AI-assisted development, data reliability, testing, documentation, observability, and cost management while contributing hands-on when needed.

The Data Analyst position requires U.S. citizenship and that all work be performed within the continental United States, Alaska, or Hawaii. The listed annual pay range is $90,000 to $110,000.

Develop and maintain Palantir Foundry data pipelines, transformations, Ontology models, workflows, data products, and user-facing applications. Integrate structured and unstructured data from enterprise systems and cloud platforms using Python and SQL. Implement data quality, governance, metadata, lineage, testing, and validation practices while collaborating with technical and business stakeholders. Support Agile development, documentation, modernization, AI-enabled analytics, troubleshooting, and federal data solutions.

Clean, standardize, enrich, and import product data into the PIM while maintaining data integrity and governance standards. Oversee bulk ingestion processes, leverage AI and automation, support data model improvements, resolve product listing issues, and contribute to data hygiene and workflow modernization. The role also involves collaborating with client-facing teams, documenting processes, proofreading product data, communicating progress, and adapting to changing priorities.