Top Data & Analytics Jobs in Fayetteville, AR

The Data Engineer will build and maintain scalable data pipelines, improve ETL processes, collaborate with AI/ML teams, and contribute to engineering culture.

Design, build, and maintain Workday reports, dashboards, Adaptive Planning sheets, and automations. Deliver workforce analytics, forecasts, and visualizations to support workforce planning and data-driven HR decisions. Collaborate to develop scorecards and influence business outcomes with real-time and forecasted people data.

Design and analyze experiments, measure campaign incrementality, identify customer segments and engagement opportunities, validate tracking and anomalies, surface actionable insights, and build scalable measurement infrastructure with cross-functional partners.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Partner with cross-functional teams to design experiments, analyze large datasets, build dashboards and metrics, identify trends and customer behaviors, improve data quality and instrumentation, and provide actionable recommendations that drive strategic decisions and operational improvements.

Work with public safety agencies to ensure NIBRS compliance by analyzing incident and records data, identifying/reporting issues, implementing state-specific reporting solutions in the Mark43 platform, and collaborating with cross-functional teams to improve data quality and customer outcomes.

Designs, develops, and delivers BI and analytics solutions (reports, dashboards, data marts, cubes). Analyzes requirements, architects data structures, mentors junior staff, evaluates BI/visualization technologies, and supports production troubleshooting and stakeholder communication.

Work across data infrastructure and analytics: build and maintain dbt models, ingest and transform data, create dashboards and semantic layers in Power BI, validate AI-generated code, partner with stakeholders to deliver analyses and data products, and improve data governance and documentation.

Build and maintain revenue and customer-lifecycle reporting, author complex BigQuery SQL, develop segmentation and clustering models in BigQuery ML, perform entity resolution and data quality reconciliation, migrate and maintain Tableau dashboards, and deliver ad-hoc and recurring analyses to support Sales, Revenue, and cross-functional teams.

Lead design and implementation of large-scale data platforms and pipelines using Redshift, ADF, Hadoop/Hive, Spark/Scala, Snowflake, Databricks, and GCP. Drive architecture decisions, performance tuning, and best practices for big data processing and storage.