Top Senior Data & Analytics Jobs in Huntsville, AL

The Senior Data Scientist will analyze and optimize marketing funnels, build statistical models, conduct experiments, collaborate with teams, and mentor junior members.

Own and build audit-ready data architecture, ETL pipelines, and validations to support internal audit. Maintain inventories, playbooks, and catalogs; assess downstream impacts of schema changes; implement automated data quality checks and monitoring; and translate audit/business requirements into technical specifications for stakeholders.

Partner with GTM leaders to turn large datasets into actionable insight, build dashboards and forecasting models, analyze pipeline/retention/productivity, and implement automation and AI-enabled workflows to improve revenue performance and GTM operations.

Partner with cross-functional teams to design experiments, analyze large datasets, build dashboards and metrics, identify trends and customer behaviors, improve data quality and instrumentation, and provide actionable recommendations that drive strategic decisions and operational improvements.

Design, build, and optimize scalable batch and streaming data pipelines. Model and process structured and unstructured data, ensure production reliability and observability, apply ML techniques for insight extraction, and drive data strategy while adopting modern tooling and IaC practices.

Design and analyze experiments, measure campaign incrementality, identify customer segments and engagement opportunities, validate tracking and anomalies, surface actionable insights, and build scalable measurement infrastructure with cross-functional partners.

Build and own data platform infrastructure and scalable pipelines (ingestion, orchestration, transformation, delivery). Define governance, observability, and AI-first architecture. Optimize performance, ensure data quality, mentor engineers, and integrate AI-assisted tooling.

Design, build, and operate scalable PostgreSQL databases and cloud-native data infrastructure. Build and maintain ETL/ELT pipelines, optimize query and server performance, ensure high availability and disaster recovery, improve observability, troubleshoot production issues, guide schema and application design, evaluate database technologies, and mentor junior engineers to support reliable, secure data-driven applications.

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.

Own and evolve the data platform: architect, build, and maintain data models, pipelines, and access layers. Ensure data quality, governance, and reliability; monitor and optimize infrastructure; provide technical leadership, code reviews, and collaborate with cross-functional teams to deliver scalable data solutions for operations and analytics.