Top Senior Data & Analytics Jobs in Birmingham, AL

Lead design, development, testing, and delivery of Qlik-based dashboards, reports, and healthcare applications. Build data extracts, optimize Qlik apps, develop NPrinting reports, write specifications and code, use Agile tools, support deployments, and train/assist end users and QA.

Build automated enterprise reporting across clinical, operations, claims, and risk adjustment; answer ad-hoc SQL questions; design ETL and data marts with engineering; ensure data quality and documentation; develop clinical business logic and regulatory/PACE reports; mentor analysts and set reporting standards.

Analyze commercial data for sales, marketing, service and support to create metrics and insights for optimization. Collaborate with cross-functional teams to provide data-driven recommendations and manage business intelligence tools.

The Databricks Architect leads data engineering solutions, designing scalable Databricks platforms and managing cloud implementations. They work with clients, ensuring technical alignment and project execution.

As Tokenization Lead, you will manage the development and integration of tokenized real-world assets on the Monad blockchain, overseeing issuer onboarding and ensuring market liquidity.

The Sr. Data Engineer will build and maintain data pipelines, develop ETL processes, and optimize data infrastructure, collaborating across teams to ensure data reliability and performance.

The Director of Business Strategy & Intelligence will lead the BI function, provide strategic growth insights, improve pipeline intelligence, and enhance executive-level reporting to drive decision-making and business growth.

The Principal Business Analyst will lead policy administration implementations, translate business requirements, analyze regulatory updates, and support scalable insurance solutions, ensuring compliance and operational efficiency.

Lead and manage data science teams to build models and drive business solutions; oversee compliance analytics and ensure data quality.

Design, build, and maintain scalable ETL/data pipelines across distributed systems. Ensure data quality, integrity, security, and high availability. Monitor and optimize pipeline performance, perform root cause analysis, document systems, collaborate with global teams, and participate in on-call rotations to support production data systems.