Top Remote Analysis Reporting Jobs in Des Moines, IA

Analyzes and maintains customer, item, and configuration master data using Oracle and Microsoft tools. Organizes and validates files for electronic updates, investigates data and process issues, evaluates business impacts, prepares reports, and supports cross-functional projects. Collaborates with business teams to ensure data integrity, accurate national coding, efficient processes, and customer-focused solutions.

Build data foundations and end-to-end pipelines, research and implement quantitative pricing, market-making, and risk models for prediction markets, model cross-market dependencies and parlays, develop backtesting/simulation frameworks, monitor model performance and collaborate closely with traders to improve pricing and trading outcomes.

Own Hercules’ full data stack, including ETL from third-party providers into BigQuery, data modeling with dbt and medallion architecture, semantic-layer metric definition, and self-service business intelligence in Omni. Build reliable, maintainable systems and dashboards while applying strong software architecture, API design, code quality, and AI-assisted development practices.

Build and expand the company’s analytics data stack using Looker, LookML, dbt, BigQuery, and Airbyte. Develop data models, integrate multiple business systems, create KPI dashboards, and analyze product usage, customer health, adoption, and revenue data. The role empowers business teams with self-service analytics, actionable insights, and data-informed decision-making while developing a strong understanding of business metrics.

Conduct open-ended research on markets, companies, products, funding, competitors, technologies, people, and regulations. Transform findings into clear, sourced matrices, briefs, landscape maps, and one-pagers with actionable points of view. Use AI tools and lightweight scripts or scrapers to accelerate research, manage multiple shifting requests, and communicate concise conclusions to leadership.

Designs and maintains healthcare analytics infrastructure, production data models, semantic layers, and transformation pipelines using advanced SQL and analytics engineering practices. Integrates payer claims, EMR, clinical, attribution, quality, and operational data. Performs ad hoc analysis, defines standardized healthcare metrics, validates data quality, optimizes queries, documents data flows, and partners with clinical, operational, IT, and payer stakeholders to support value-based care and enterprise reporting.

Lead product experimentation and analytics across three product squads. Design experiments, define product metrics, analyze patient and clinician behavior, build dashboards, apply causal inference, and communicate actionable insights. Partner with product, engineering, design, clinical, operations, and data teams to improve instrumentation, data quality, and evidence-based healthcare product decisions.

Build and maintain automated ETL/ELT data pipelines, improve data quality and monitoring, optimize Postgres and BigQuery schemas and queries, develop internal tooling, support data governance (HIPAA), participate in on-call rotation, and collaborate across engineering teams to scale data systems.

Design and implement scalable, secure enterprise data solutions on Databricks and Azure using Delta Lake and Medallion Architecture. Lead and mentor data engineering teams; define integration patterns, governance, security (Unity Catalog, RBAC, masking, row/column-level security), and CI/CD/IaC practices. Ensure data quality, lineage, monitoring, and optimize Spark/Delta workloads for performance and cost while aligning solutions with business needs.

Design and implement end-to-end cloud data solutions, lead or mentor engineering teams, ensure performance, security, and scalability, integrate diverse data sources, write and optimize SQL, program in Java/Python/Scala, produce presentations and detailed solution documentation, and engage directly with clients to deliver production-ready systems.