Top Senior Data & Analytics Jobs in Huntsville, AL

Own Silver and Gold medallion-layer modeling and semantic layer governance using dbt and SQL. Improve warehouse performance and cost, standardize BI tooling, collaborate with stakeholders to produce trusted metrics, troubleshoot data quality, and evolve analytics platform.

Administer, secure, optimize, and modernize enterprise database environments supporting mission-critical Army aviation applications. Responsibilities include SQL Server performance tuning, patching, vulnerability remediation, backups, disaster recovery, cloud migration, compliance with DISA STIGs and RMF controls, documentation, audit readiness, and collaboration with infrastructure, cybersecurity, application, and engineering teams.

The Senior Manager leads Power BI reporting and analytics functions, overseeing a team and ensuring standardized, scalable reporting solutions while managing transition to Microsoft Fabric.

Collects, validates, and analyzes operational, logistics, readiness, inventory, and supply-chain data. Leads statistical, trend, causal, predictive, and prescriptive analysis; develops dashboards, reports, scorecards, and executive briefings; supports data integration, system testing, process improvement, KPIs, and strategic decision-making. Collaborates with Army, logistics, procurement, and program stakeholders to improve medical materiel visibility, asset accountability, and supply-chain responsiveness.

Build and maintain secure data lifecycles, pipelines, databases, applications, and executive dashboards using Palantir Foundry and Microsoft Power Platform. Transform and integrate enterprise datasets, automate workflows, apply AI capabilities, and modernize legacy processes. Translate stakeholder needs into scalable solutions, present technical findings, document procedures, and support data-driven decision-making for Army mission partners. The role requires collaboration with technical, military, civilian, and contractor stakeholders while managing multiple priorities and deadlines.

Develop and maintain cloud-based data pipelines, ingestion workflows, data dictionaries, data governance standards, dashboards, and data quality automation. The role includes SQL and Python development, cloud data warehouse administration, cost optimization, data lineage documentation, security controls, disaster recovery procedures, and collaboration with government stakeholders. The analyst will implement DataOps and GitOps practices while supporting secure, resilient data flows and cloud-native analytics environments.

Serves as the technical anchor for a database administration team supporting a defense contract. Installs, configures, maintains, secures, and optimizes Oracle, DB2, Cassandra, MongoDB, and SQL databases across cloud and containerized environments. Develops backup and disaster recovery strategies, manages capacity and audits, troubleshoots performance issues, and guides database architecture. Coordinates with developers and business stakeholders, evaluates new technologies, and mentors DBAs while supporting AWS, Azure, Kubernetes, and Docker deployments.

Conduct independent cost analysis and develop lifecycle cost estimates for Army acquisition programs. Forecast future system and program costs, create methodologies and models, advise on budgets and resource allocation, analyze Earned Value Management reports, and prepare executive briefings and milestone-review documentation. The role requires ACE-IT modeling, Army acquisition knowledge, strong communication, independent judgment, and an active Secret clearance in Huntsville, Alabama.

Leads enterprise data architecture initiatives for the U.S. Army Contracting Command. Responsibilities include engineering and modeling large datasets, developing pipelines and predictive models, designing APIs, implementing governance and security standards, reporting KPIs, managing data platforms and catalogs, presenting insights to leadership, and leading data literacy training and continuous improvement efforts.

Design, build, and maintain scalable data pipelines, warehouses/lakes, and platforms. Lead multidisciplinary teams to implement ETL/ELT (batch and streaming), optimize data lake performance, enforce data governance, and support analytics and ML use cases on cloud and on-prem environments.