Top Data & Analytics Jobs in Fayetteville, AR

Leads the analytics function, develops team talent, oversees client measurement plans, dashboards, reporting, insights, and optimization recommendations. Partners with media, platform, client service, and operations leaders to deliver holistic measurement programs. Manages account workloads, client onboarding, business reviews, analytics productization, measurement partnerships, training, and complex data analysis. Requires extensive analytics, client management, visualization, multi-touch attribution, and media mix modeling experience.

Develop and own healthcare-related data analyses, financial models, databases, and data resources. Write Python and SQL code, validate results, perform data quality audits, identify anomalies, and maintain data integrity. Create reports, presentations, diagrams, and engineering requirements documents, while partnering with strategy leads and cross-functional stakeholders to design data-informed technology solutions. Support client projects, communicate findings, and ensure accurate, compliant deliverables.

Build and maintain ETL and data pipelines using Python, PySpark, and AWS services. Orchestrate workflows, develop event-driven integrations, optimize data storage and queries, process API and JSON data, and implement data quality monitoring. Support CI/CD, production operations, cloud migration, data lake and lakehouse initiatives, and near-real-time systems while collaborating with stakeholders to deliver technical solutions.

Designs and governs PANTHERx’s semantic layer on Databricks, including Unity Catalog metric views, Gold-layer tables, promotion logic, and reusable data products. Establishes canonical, versioned business metrics for BI, analytics, partner feeds, and AI inputs. Responsibilities include data modeling, migration, validation, observability, documentation, governance, stakeholder collaboration, and mentoring analytics engineers. The role requires advanced SQL, Python, and PySpark skills, strong Databricks expertise, and experience operating across analytics engineering and data engineering.

Builds, operates, and owns enterprise data warehouse pipelines and models on Databricks. Develops Delta Lake batch and streaming pipelines across Bronze, Silver, and Gold layers; implements data quality, reconciliation, observability, governance, and performance improvements. The role owns assigned data domains, supports event-driven ingestion, documents architecture and runbooks, responds to incidents, collaborates with QA and governance teams, and mentors data engineers.

Lead the Ads Signals & Measurement data engineering team across conversion and attribution, measurement foundations, audience onboarding, and identity. Set cross-organizational technical direction, resolve scalable data architecture decisions, mentor engineers, and partner on platform-wide initiatives. The role requires expertise in modern data stacks, advertising technology data flows, privacy and governance, distributed systems, and emerging AI technologies.

Own trade performance reporting, dashboards, scorecards, promotional ROI analysis, range review support, category insights, and sales projections for major retail customers. The role turns sales and shopper data into commercial recommendations, supports retailer presentations and new product launches, and collaborates with Sales, Marketing, Supply Chain, Demand Planning, and Finance. It requires strong Excel and presentation skills, commercial curiosity, attention to detail, clear communication, and the ability to manage multiple priorities.

Organize and curate large volumes of raw information: extract key points from transcripts, maintain clean spreadsheets, curate links/resources, tag and categorize content, and follow or propose systems for information structure. Part-time remote role with initial 10 hours/week and potential to grow.

Reviews, develops, validates, and refines dashboards, reports, visualizations, calculations, data sources, KPIs, and analytical workflows across BI platforms. The role documents findings, provides structured feedback, troubleshoots reporting accuracy, and evaluates AI-powered agents and workplace connectors used in analytics processes.

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.

Organise and curate large amounts of raw material: extract key points from transcripts, collate and maintain clean spreadsheets, tag and categorise links and documents, and create findable information structures following or suggesting systems.