Top Remote Data & Analytics Jobs in Omaha, NE

As a Pricing Manager, you will lead pricing initiatives, manage A/B tests, perform financial analysis, and collaborate with stakeholders to optimize pricing strategies and revenue goals.

The Director of Growth Strategy & Analytics will lead analytics efforts, develop strategies for consumer engagement, and improve app experiences through data insights and collaboration with teams, utilizing AI tools for automation.

The Forward Deployed Marketing Data Scientist will work with AI customers and engineering teams to optimize AI-driven marketing campaigns through data analysis, diagnostics, and communication of insights to stakeholders.

As a Senior Data Engineer, you'll define data ontology, collaborate with teams, design data pipelines, and optimize data infrastructures to support analytics for Yahoo Mail.

Lead BI and analytics for Listings, Marketing, and Media: own performance reporting and dashboards, run ad-hoc analyses, build forecasts, define KPIs, and translate findings into executive-ready recommendations while partnering across Product, Data, Finance, Marketing and GTM teams.

Design and maintain a dbt-based business data layer for GTM metrics, centralize and reconcile multi-source data, implement automated data quality and reconciliation checks, align and document metrics with stakeholders, mentor analytics team, and lead root-cause investigations into complex data anomalies.

Lead development and scaling of financial analytics: build data models, dashboards, and reporting; translate financial data into executive insights; embed predictive analytics; partner with Finance, IT, and business units to improve data quality, governance, forecasting, and automation.

Build and operate data-intensive web products and APIs, extend high-throughput ETL pipelines and scrapers, ensure reliability/observability, design self-scaling services, participate in code review, and collaborate across product, data, and infrastructure teams to meet production SLAs.

Design and implement enterprise data architectures and lakehouse/warehouse solutions using Microsoft Fabric, Databricks or similar platforms. Lead data modeling, ETL/ELT pipelines, cloud integration, CI/CD, and stakeholder-facing consulting engagements to deliver scalable, secure analytics systems.

Own and implement the canonical data model and governance for a multi-tenant MEP SaaS platform. Architect data for AI/ML readiness (RAG, embeddings, vector search), design polyglot persistence and lake/lakehouse pipelines, lead staged modernization and migrations, produce hands-on prototypes and in-repo guardrails, and partner with platform, DB engineering, and ML teams to ensure data quality, lineage, and observability.