Top Data & Analytics Jobs in Fayetteville, AR

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.

Design, build, and maintain large-scale data pipelines and ETL/ELT processes using Redshift, Azure Data Factory, Hadoop/Hive, Spark/Databricks, and Snowflake on cloud platforms (GCP). Implement Scala-based data processing, optimize performance, and support analytics and data warehousing needs.

Analyze and combine disparate marketing and analytics data, create reproducible reports and visualizations, collaborate with data engineers/scientists and stakeholders, derive insights and recommendations for clients, and improve reporting templates and workflows.

Build and own data platform infrastructure and scalable pipelines (ingestion, orchestration, transformation, delivery). Define governance, observability, and AI-first architecture. Optimize performance, ensure data quality, mentor engineers, and integrate AI-assisted tooling.

Produce and validate default reporting and analytics for mortgage servicing portfolios. Investigate data discrepancies, perform root-cause analysis, modify reports for ad-hoc needs, document processes, and collaborate with default management to ensure regulatory and investor-compliant reporting.

The Senior Data Engineer will maintain and improve data infrastructure, design ETL processes, and create high-performance pipelines for analytics and AI initiatives using SQL and Python in cloud environments.

The Associate will generate insights, analyze data for better decision-making, enhance operational dashboards, and collaborate across teams to improve efficiency and report to leadership.