Top Data & Analytics Jobs in Fayetteville, AR

The Director of Cloud FinOps will manage financial operations related to public cloud, optimize costs, and partner with various teams to maintain efficiency and profitability.

Analyze business performance, provide insights, improve processes, participate in continuous improvement projects, and collaborate with cross-functional teams.

The Senior Clinical Trials IT Business Analyst bridges Clinical Development and IT, optimizing clinical trial technologies and managing system implementations, validations, and stakeholder engagement.

Develop and maintain Python-based data applications and pipelines: fetch data from databases/APIs/files, build Pandas DataFrames/NumPy arrays, write complex SQL and data transformations, handle nested JSON, and collaborate with data science teams to deliver production data platforms.

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.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.

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.

Lead design and ownership of ZoomInfo's PLG measurement system, define KPIs and leading indicators, analyze end-to-end customer journeys, diagnose growth issues, and influence product investments. Build AI-native, automated analytics workflows, reporting, and monitoring while partnering cross-functionally to prioritize experiments and scale insights that drive adoption, retention, monetization, and expansion.

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.