Top Analysis Reporting Jobs in Little Rock, AR

Analyze datasets to generate reports and visualizations that inform business decisions. Produce regular reporting, create data visualizations, and work cross-functionally to support data-driven strategies with attention to accuracy.

Design, implement, and optimize Snowflake data storage and ETL solutions. Write and tune SQL, integrate data sources and BI tools, ensure data security and compliance, and collaborate with teams to meet business objectives.

Develop and maintain Python-based data applications and pipelines: fetch data from databases/APIs/files, build Pandas DataFrames/NumPy arrays, write complex SQL and data transformations, handle nested JSON, and collaborate with data science teams to deliver production data platforms.

Lead development and scaling of financial analytics: build data models, dashboards, and reporting; translate financial data into executive insights; embed predictive analytics; partner with Finance, IT, and business units to improve data quality, governance, forecasting, and automation.

The Senior Data Engineer will design and build data pipelines and infrastructure to support data science and business intelligence solutions, utilizing AWS services and streaming technologies.

The Senior Data Engineer will design and implement lakehouse architectures, optimize ClickHouse deployments, develop ETL/ELT pipelines, and create data models to support analytical and operational functions.

Lead the analytics team for the third-party agent business, driving business strategy, product analytics, and AI-powered insights while fostering cross-functional partnerships.

The Director of Cloud FinOps will manage financial operations related to public cloud, optimize costs, and partner with various teams to maintain efficiency and profitability.

Own and implement the canonical data model and governance for a multi-tenant MEP SaaS platform. Architect data for AI/ML readiness (RAG, embeddings, vector search), design polyglot persistence and lake/lakehouse pipelines, lead staged modernization and migrations, produce hands-on prototypes and in-repo guardrails, and partner with platform, DB engineering, and ML teams to ensure data quality, lineage, and observability.

Lead analytics and tooling initiatives to drive operational excellence for global data-center construction and infrastructure. Translate business requirements into data products, build foundational datasets and KPIs, develop dashboards and automated reporting, run advanced statistical and ML analyses, and mentor stakeholders to improve performance measurement, governance, and decision-making.