Top Data & Analytics Jobs in Little Rock, AR

The Senior Analyst will support product engineering efforts by analyzing digital solutions, enhancing user experiences, and collaborating across teams to deliver insights and improvements.

No job responsibilities were provided. The posting requires U.S. citizenship or naturalized citizenship and that all work be completed within the United States (including Alaska and Hawaii). Pay range: $95,000–$110,000 annually.

Provide technical and administrative support to leadership: monitor sprints and Scrum synchronizations, perform technical research, write Python scripts for automation and API testing, manage and report data using advanced Excel, and prepare meeting summaries and cross-functional coordination.

Lead analytics and insights for the CFO and exec team: produce executive-ready analyses, design scalable analytics infrastructure, leverage AI to accelerate workflows, partner cross-functionally to drive strategy and execution, and manage multiple high-impact initiatives.

Lead a team of data engineers to design, build, and maintain scalable data pipelines, a Data Vault, data warehouses and marts. Own backlog, sprint planning, mentoring, stakeholder collaboration, data validation/monitoring, and platform improvements to deliver key metrics and data infrastructure across the business.

Lead analytics strategy for federal programs: perform statistical modeling, forecasting, and data mining; build dashboards and automated workflows; ensure NIST/FISMA compliance and data quality; present findings to government stakeholders; mentor junior analysts and manage analytics workstreams.

The Technical Enablement & Documentation Lead is responsible for developing and maintaining product documentation, creating a certification program, and collaborating with teams to improve the knowledge experience for Flosum's users.

Design and own end-to-end data platform architecture, build ingestion and transformation pipelines, model multi-tenant datasets, optimize Postgres and ClickHouse performance/cost, implement orchestration and observability, define data quality and reconciliation standards, and mentor data/product engineers.

Design, implement, and manage scalable multi-cloud data platforms and ELT pipelines (AWS/Azure). Build and optimize Snowflake data models, dbt transformations, and Airflow orchestration. Define data engineering standards, enforce governance and quality, collaborate cross-functionally, and mentor global/offshore teams.

The Senior Data Engineer will build and maintain ETL/ELT pipelines, optimize SQL queries, and collaborate on machine learning workflows, driving data engineering best practices.