Top Data & Analytics Jobs in Omaha, NE

Leads advanced analytics initiatives supporting sales, marketing, and operations strategy. Develops statistical and predictive models, dashboards, KPI reporting, and customer analyses using large datasets. Partners with stakeholders and data engineering teams to translate business questions into actionable insights, communicates findings to executives, and mentors junior analysts.

Lead analytical support for performance marketing by evaluating CAC, ROAS, LTV, conversion, retention, and acquisition efficiency. Conduct deep-dive analyses, experimentation, incrementality studies, and marketing measurement using SQL, Python, and visualization tools. Build scalable reporting frameworks, improve data quality, communicate insights to senior stakeholders, influence channel and budget decisions, and mentor junior analysts.

Architects FHIR-compliant clinical data models and develops harmonization, enrichment, and validation strategies across EHR, HIE, and claims data. Maintains clinical ontologies and value sets, ensures data accuracy and longitudinal integrity, and documents technical requirements for engineering teams and stakeholders. The role requires advanced Python and SQL skills, healthcare interoperability expertise, and experience with clinical informatics or data integration.

Build and optimize scalable Databricks data pipelines across a medallion architecture. Develop data models, implement data quality checks and validation, integrate Azure services, and ensure data accuracy, governance, lineage, security, and performance. The role requires designing config-driven pipelines supporting CDC and event-based processing, maintaining CI/CD deployments, and working with structured and unstructured data across SQL and NoSQL systems.

Lead the architecture and delivery of modern data and analytics platforms for clients. Design governed, secure solutions using Microsoft Fabric, Azure, Databricks, Power BI, and Purview. Translate business needs into scalable architectures, estimates, roadmaps, and delivery plans. Guide architecture reviews, governance, CI/CD, testing, monitoring, and operational readiness while enabling AI, Copilot, RAG, and intelligent application initiatives. Serve as the technical lead and trusted advisor for client engagements.

Leads business analysis, advanced analytics, KPI development, data modeling, reporting automation, and AI/ML initiatives supporting global data-center construction and operational excellence. Builds datasets, dashboards, performance metrics, forecasts, and scenario models; translates complex findings for executives; aligns technology solutions with business needs; and promotes data governance, documentation, process improvement, and analytics maturity across cross-functional teams.

Sets technical direction and architectural coherence across Netflix’s Ads Data Engineering organization. The role guides cross-domain data system decisions, partners with engineering and business leaders, mentors data engineers, shapes platform-wide initiatives, and advances AI-native data engineering. Responsibilities span modern data foundations, ad-tech data flows, privacy and governance, platform migrations, scalable data products, and collaboration with Ads Platform Engineering, Data Science, and Product teams.

Owns production data systems end to end, including data models, ETL and API integrations, applications, platform maintenance, data quality, governance, and technical debt. Supports OPSDB and exploration operations, improves reliability and alerting, documents systems, collaborates with cross-functional and nontechnical stakeholders, and mentors junior analysts. The role also supports procurement and inventory initiatives, works with geologists, and requires occasional international travel to exploration sites.

Own Marketing’s reporting and analytics layer by building executive dashboards, defining KPIs, modeling data across GTM systems, and establishing governance and trusted sources of truth. Partner cross-functionally to measure funnel performance, attribution, campaigns, pipeline, and ROI. Help evaluate and develop AI-powered analytics, conversational reporting, automated insights, and intelligent visualization while translating complex data into actionable recommendations for leadership.

Analyze large healthcare datasets, build and implement quantitative models, perform statistical analyses, ensure data accuracy, collaborate with cross-functional teams, and provide actionable insights to improve healthcare delivery.