Top Data & Analytics Jobs in Fayetteville, AR

The Data Analyst will support operational reporting and stakeholder needs, working with SQL and Artiva to meet business requirements through data and reporting solutions.

Execute and validate donor campaign and fulfillment data operations, maintain data quality and governance, produce audience counts and reports, support fundraising analytics and performance tracking, troubleshoot data issues, and coordinate data deliverables with internal teams and vendors to strengthen donor engagement.

Implement, QA, and document analytics tags across GTM, GA4, server-side pipelines, Quantum Metric, Dynamic Yield and marketing pixels. Translate Figma into developer-ready data layers, collaborate with engineering to ensure tracking parity (web, app, Shopify), maintain pixel integrity, support experimentation piping, monthly audits, consent enforcement, and contribute to QA and solution documentation.

The Business Intelligence Analyst analyzes complex data for finance teams, develops reports and dashboards, and enhances financial reporting solutions. They collaborate with teams to ensure reporting accuracy and alignment with business needs.

Own support analytics for User Operations: build dashboards and recurring reports, track north-star metrics (cSAT, TTR, QA, escalations), instrument Zendesk, connect support to product/customer data, quantify operational costs of bugs, and measure AI-driven support performance.

The Lead Product Analyst will design experiments, ensure data quality, build dashboards, and create an experimentation framework focusing on growth and product metrics.

Lead business intelligence efforts to analyze complex data, define KPIs, identify operational inefficiencies, and recommend process improvements. Collaborate with cross-functional teams and executives to implement data-driven strategies, manage improvement projects, monitor resource allocation, and ensure compliance with policies and regulations.

The Senior Azure Data Consultant will build and maintain data pipelines, develop lakehouse solutions, optimize ETL processes, and support analytics capabilities in a Microsoft Fabric environment.

Design, build, and maintain scalable Databricks-based data pipelines and ELT workflows; develop and document dbt models; define data modeling methodology; ensure data quality, reliability, and scalability; collaborate with clients and cross-functional teams; provide technical guidance and deliver improvements to clients' data infrastructure and analytics capabilities.

Build and own the reporting and insight layer: write optimized Redshift queries, build dashboards, monitor model feedback signals, triage and prioritize investigations for data science, maintain ETL pipelines ingesting semi-structured data, and enable Customer Success with clear metrics and onboarding checks. Move into model validation and automation to scale analytic workflows.