Top Analysis Reporting Jobs in Little Rock, AR

Lead architecture and implementation of cloud-native data platforms on Google Cloud (BigQuery). Build unified batch/streaming pipelines, enforce IaC with Terraform, implement open table formats and governance (Dataplex/Data Catalog), automate data quality/lineage, partner with analytics and product teams, and mentor data engineers.

Perform part-time quality audits and evaluations of task outputs, define and refine quality benchmarks and scoring rubrics, analyze audit results to produce actionable insights and reports, and recommend process improvements to raise output quality.

Lead end-to-end payroll data integrations during client onboarding: gather requirements, configure and test inbound/outbound payroll files, create technical specifications and mappings, collaborate with clients, payroll vendors, and internal teams, perform data validation and audits, and transition clients to ongoing operations.

Lead extraction, mapping, cleaning, transforming, and importing complex donor and fundraising data from legacy systems into Virtuous. Use SQL and dbt to design ETL transformations, collaborate on migration strategy, work with customers and internal teams, and solve complex data structure and relationship issues to align legacy data with Virtuous CRM best practices.

Administer and maintain CRM and data systems (EveryAction, Salesforce, BigQuery, CARTO), respond to staff and affiliate data/tech requests, ensure data quality and de-duplication, create and deliver training materials, build network capacity, manage vendor/consultant relationships, and travel occasionally for in-person trainings and support.

Lead finance operations analytics initiatives: design scalable datasets, build analytical models and dashboards, perform complex SQL analyses (revenue, cash flow, bad debt), automate insights, and present executive-level, data-driven recommendations while influencing cross-functional teams.

Design and build scalable data engineering solutions, expand centralized ETL framework and metric definitions, develop production Python and SQL data jobs, use Spark/dbt/Fivetran/Airflow with S3, collaborate cross-functionally, and apply AI coding agents to streamline workflows.

Collect, validate, and maintain market data across asset classes; perform statistical analysis and modeling; ensure data accuracy through QA; troubleshoot discrepancies; produce reports, dashboards, and recommendations; partner with stakeholders to improve data models and analytics practices.

Manage end-to-end analytics for performance guarantees across strategic accounts: execute recovery and accrual analytics, build SQL-based pipelines and Looker dashboards, support RFPs/renewals with scenario modeling, partner with Sales/Customer Success and Data Engineering, and present technical findings to internal leaders and clients to mitigate financial risk and drive actionable insights.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.