Top Senior Data & Analytics Jobs in Huntsville, AL

Own end-to-end analytics across marketing, revenue, product, and partnerships. Build reliable data models and semantic layers in a lakehouse, maintain dashboards and monitoring, investigate anomalies, conduct experimentation, and translate complex analyses into recommendations for senior stakeholders. The role requires advanced SQL, Python, data modeling, stakeholder communication, autonomy, and mentoring, with responsibility for improving data quality and building analytical standards in a high-growth startup.

Provides data analytics and business intelligence support for government customers. Responsibilities include gathering requirements, analyzing and transforming enterprise data, designing data models, developing dashboards and visualizations, documenting governance processes, improving workflows, and training users. The role requires government acquisition, finance, or financial management experience, preferably within DoD or Air Force systems, and supports financial office operations.

Lead WEX’s semantic data platform and Data-as-a-Service strategy. Define architecture and roadmap, build trusted semantic business objects and governance capabilities, enable AI and agentic applications, and drive enterprise adoption. Lead engineers, architects, and technical leaders while partnering with Product, AI, Analytics, Risk, Finance, and business teams. Translate complex business concepts into scalable platform abstractions and oversee modernization of large-scale data ecosystems.

Lead Salesforce data migration and quality activities for a Department of Veterans Affairs modernization program. Analyze SQL Server data, create source-to-target mappings, execute ETL and Salesforce loading, validate and reconcile records, implement data quality controls, and develop migration and application test plans. Track defects, support automated monitoring and testing, collaborate with architects, developers, stakeholders, and provide migration status, risk, and quality updates.

Own GTM reporting and analytics across Salesforce, warehouse systems, Tableau, and Excel. Build trusted dashboards, define metrics, investigate data quality issues, and lead analysis for pipeline, forecasting, territory design, capacity planning, productivity, and resource allocation. Partner with GTM, CRM, Data, and Systems stakeholders to improve reporting architecture and support leadership decisions. Use AI tools to automate analysis and develop internal analytics workflows.

Build and own the data platform backbone: design ingestion patterns, Snowflake warehouses, governance, and freshness strategy. Implement reliable batch and streaming pipelines, data quality, observability, and onboarding processes. Lead legacy migrations, create data contracts and SLAs, and apply AI-native tooling to automate debugging, documentation, and operational workflows while partnering with Analytics, Engineering, and vendors.

Drive revenue operations analytics by building reliable data models and dashboards, querying large datasets in Snowflake, ensuring data integrity across the revenue tech stack, and delivering strategic insights to Sales, Marketing, and Customer Success using Looker, Domo, SQL, and scripting.

Transform commercial, market, consumer, and portfolio data into actionable insights. Build and maintain dashboards and KPI reporting, analyze performance and competitive trends, support pricing, assortment, and launch decisions, and deliver executive-ready recommendations while partnering with cross-functional teams to ensure data quality and commercial alignment.

Design and own a federated, multi-institution medallion lakehouse on Azure Databricks and Microsoft Fabric. Define federated multi-tenant architecture, Unity Catalog security, data ingestion from ERP/SIS/LMS/CRM/Workday, and platform standards. Provide hands-on architecture guidance, review designs, document decisions, and partner with governance, delivery, and engineering teams to enable production analytics at multiple institutions.

Design and build Snowflake transformation layer and migrate legacy SQL to versioned dbt models. Define conformed dimensions/facts using Kimball principles, set modeling and CI/CD standards, implement data quality/lineage, support BI migration and AI/ML readiness, and mentor future hires. Hands-on work in dbt, SQL, and Python with stakeholder collaboration and governance for financial and operational data.