Top Remote Analysis Reporting Jobs in Omaha, NE

Leads WWT’s Data Reliability and AI Readiness pillar, setting enterprise AI data strategy and standards for trustworthy, reusable data. Oversees certification, lineage, quality SLAs, readiness scoring, data products, dashboards, and AI-powered reporting. Coordinates IT, AI engineering, analytics, business, and data teams on enterprise initiatives. Manages a Product Owner and engineers, improves operational data, promotes certified data products, and translates internal AI and data capabilities into customer-facing value.

Leads WWT’s Data Reliability and AI Readiness pillar, establishing enterprise AI data strategy, governance, certification, lineage, quality standards, and readiness scoring. Coordinates cross-functional data initiatives, improves operational data, owns trusted data products and AI-powered reporting, and manages a product owner and engineering team. Partners with IT, AI engineering, analytics, and business teams to deliver reliable, reusable, production-ready data while improving data economics and translating internal capabilities into customer-facing offerings.

Owns the end-to-end architecture, development, infrastructure, data pipelines, and Power BI reporting platform supporting data governance, informatics, analytics, auditing, and data quality. Leads and mentors a data engineering team, defines schemas and engineering standards, ensures security and HIPAA compliance, oversees testing and Agile delivery, manages stakeholder requirements, and remains hands-on with backend technologies, data models, Power BI, and DAX.

Design and maintain healthcare data integration pipelines, models, and validation processes for claims, billing, clinical, pharmacy, EMR, FHIR, and value-based care data. Collaborate with clients and internal analytics, product, and customer success teams to interpret data, document business rules, support implementations, and build reusable Ursa data models. Apply healthcare domain expertise, data security practices, HIPAA compliance, and appropriate judgment when using AI-assisted tools.

Senior individual contributor who designs, develops, optimizes, and maintains complex SQL data solutions and Microsoft SQL Server instances. Leads data modeling, performance tuning, schema design, and data quality efforts; partners with engineering, ETL, BI, and product teams; drives standards, architecture, governance, and compliance for scalable, high-performance data platforms.

Lead design of end-to-end analytics and data solutions, produce architecture diagrams and technical designs, guide delivery teams, run client discovery and requirements sessions, support pre-sales and proposals, build reusable frameworks, and manage and mentor a delivery team to ensure quality and alignment to architecture.

Design, build, and maintain scalable data pipelines and integrations across AWS, Azure, and BigQuery. Normalize, aggregate, and ensure data quality for large web and transactional datasets, leveraging APIs, ETL/orchestration tools, and big-data technologies to support analytics and BI in an e-commerce environment.

Lead performance investigations across the data product stack to diagnose and fix slow queries and UX issues. Design data architecture changes, build benchmarks, measure latency/throughput/cost (ClickHouse Cloud), prototype solutions, instrument monitoring, and partner with product and engineering to balance responsiveness, scalability, and cost.

Lead end-to-end product analytics: instrumentation, data quality, funnels, retention, and experimentation. Use SQL and Python for analysis, build dashboards, partner with product and growth, and improve analytics infrastructure (Amplitude and data warehouse migration). Remote with GMT+1 overlap.

Lead analytics to improve player experience, engagement, retention, and monetization. Analyze player lifecycle, run cohort and funnel analyses, design and evaluate A/B tests, build dashboards, define product metrics, investigate KPI changes, and partner with product, marketing, engineering, and data teams to deliver data-driven recommendations and improve data quality.