Top Business Intelligence Jobs in Little Rock, AR

Lead integration of technology into information systems, design data warehouse and BI capabilities, define data architecture and dictionaries, centralize disparate data, design dashboards, document system architecture, perform data quality and management, and provide solution engineering, pilots, and enablement for analytics and resource management.

Design, build, and maintain large-scale data pipelines, ETL/ELT processes, and data models. Collaborate with analysts, architects, and data scientists to deliver BI solutions, optimize performance, support production systems, and mentor team members. Implement cloud and on-prem data architectures, CI/CD practices, and tooling to enable data-driven decision-making across the business.

Lead enterprise data governance, quality, MDM, cleansing, validation, reconciliation, and migration efforts to support ERP implementations and large transformation programs. Develop governance frameworks, coordinate data readiness and testing, produce executive reporting and presentations, manage project plans and governance artifacts, and drive stakeholder alignment and change management.

Lead design and build of ETL pipelines and Gold Layer tables in Databricks; develop semantic layers, data dictionaries, and AI-ready documentation; create dashboards and ad-hoc analyses to surface marketing and sales KPIs; partner with stakeholders to translate requirements into analytics-ready datasets and enable self-serve BI and agentic AI workflows.

The Data & Accounting Analyst will analyze financial and marketing data, create detailed reports, and ensure accuracy in financial data to support strategic decisions.

Transform data into actionable insights by building dashboards, reports, and visualizations. Partner with cross-functional teams and data engineering to ensure data quality, lineage, and AI-ready metadata. Audit datasets, define monitoring rules, document data dictionaries, pilot AI-assisted BI tools, and apply hypothesis-driven analysis to surface insights that inform business decisions.

Build AI-augmented BI dashboards, semantic layers, and AI-ready metadata. Use AI-assisted tools to accelerate SQL and dashboard development, productionize ML outputs into BI, enforce data quality and governance, and present insights to business stakeholders including C-suite.

The Director of Data and Enterprise Applications oversees the architecture, development, and support of business applications and data platforms, driving digital transformation and ensuring data integrity and accessibility.

Own and operate the Microsoft Fabric and Power BI platform end-to-end: administer tenants, capacities, OneLake, and governance; build secure data integration pipelines and access layers for BI and AI agents; automate CI/CD and platform operations; enforce security and data governance; and translate business requirements into technical designs while liaising between IT, security, and business stakeholders.

Analyze healthcare and operational datasets to create, validate, and maintain reports and dashboards using SQL, Excel, and BI tools. Support utilization, cost containment, regulatory reporting, and ad hoc analyses. Collaborate with stakeholders to define requirements, document workflows, and deliver actionable recommendations.

Lead GTM strategy and analytics to build headcount/capacity models, territory optimization, quota setting, predictive models, and BI reporting. Partner with Sales, Marketing, Finance, and Data to inform planning cycles, monitor pipeline and productivity, and deliver executive-level insights for growth and investment decisions.

The Senior Data Analyst oversees performance reporting tools, automates data pipelines, conducts quantitative analyses, and communicates findings to various stakeholders.

Lead architecture and delivery of enterprise data transformation on the Guidewire Data Platform. Drive design, ingestion/egress, migration performance, and AI-enabled tooling. Facilitate inception and design review sessions, mentor teams, coordinate with partners, and ensure successful data platform adoption and repeatable delivery practices while spending significant time on customer sites.

Lead design, development, automation and maintenance of BI products (dashboards, datasets, semantic layers). Use SQL/SAS (and Python) for data validation, optimize BI performance, translate requirements into technical solutions, document metrics, apply security rules, and consult stakeholders to drive measurable business outcomes across DV&L platforms.

Lead design, development, automation and maintenance of BI products (dashboards, datasets, semantic layers). Translate stakeholder requirements into governed, performant BI solutions using SQL, SAS and BI tools; optimize performance, document metrics, apply access controls, and train teams to drive adoption and measurable business outcomes.

Lead design, development, automation, and maintenance of BI products for Health & Wellness. Build dashboards, datasets, semantic layers, and standardized reports using SQL and SAS, partner with stakeholders to translate requirements, ensure performance and governance, optimize BI solutions, document definitions, and train teams while supporting cloud/AI initiatives.

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.

Lead product analytics efforts to define KPIs, build measurement frameworks, analyze customer behavior, and generate insights that influence product and engineering decisions. Partner with Product, Engineering, and Data teams to design event tracking, run experiments, quantify opportunity sizes, and communicate recommendations through clear narratives and visualizations to drive product adoption, retention, and business outcomes.

Lead ownership of BI reporting infrastructure: build and standardize dashboards, extract insights from messy third‑party data, partner with marketing teams to drive performance optimization and deliver proactive retrospective analyses that influence business decisions.

Lead BI developer owning end-to-end reporting for performance marketing verticals. Build and standardize dashboards, author LookML models, extract insights from messy third-party data, partner with Yield/Paid Media/Account teams, deliver retrospective analyses, and drive adoption and business impact.

Lead BI Developer owns reporting infrastructure end-to-end, building standardized, trusted dashboards and LookML models, analyzing messy third-party data, partnering with Yield/Paid Media/Account teams to deliver actionable performance marketing insights and retrospective analyses that drive business decisions.

The Senior Consultant will lead the design and implementation of data solutions using Microsoft Fabric, Power BI, and Databricks to enhance analytics capabilities for clients. They will engage with stakeholders to define data strategies and deliver high-quality consulting services across multiple projects.

Build and maintain a scalable BI and reporting platform using ClickHouse and Python ETL. Design dimensional models and reporting marts, optimize queries, create dashboards, support data pipelines from Elasticsearch, SQL Server, APIs and files, and add AI-enabled reporting features and developer tooling for analytics workflows.

Lead the architecture and development of CareDx's enterprise BI ecosystem. Own Power BI modeling, DAX optimization, governance (RLS, deployment pipelines), and self-service enablement. Collaborate with data engineering to build scalable Databricks/Delta Lake/PySpark pipelines, leverage Microsoft Fabric and Lakehouse architecture, mentor BI developers, translate business needs into analytics solutions, and drive BI performance and reliability.

Perform quantitative and qualitative analysis, build reports and dashboards, produce datasets, troubleshoot data issues, and present findings to stakeholders. Collaborate across teams and third parties to define reporting specs, improve data quality, and recommend KPIs and best practices to support decision-making.