Top Senior Data & Analytics Jobs in Huntsville, AL

As a Staff Data Scientist at SentiLink, you will develop fraud detection models, conduct analyses, collaborate across teams, and drive the development of financial risk products.

As a Staff Product Analyst, you'll define analytics strategies, build measurement infrastructure, design experiments, and partner with product teams to boost self-serve conversion and product adoption.

The Senior Analytics Engineer will develop data pipelines, build models, and create dashboards to provide actionable insights for various teams. The role requires collaboration with multiple stakeholders to meet analytical needs and ensure data governance.

Design, build, and operate large-scale data platforms and Spark/PySpark pipelines. Enable data integration, modeling, quality, and observability. Build MCP servers and AI-augmented tooling, mentor engineers, and lead cross-functional projects to deliver reliable data products.

Own and architect large-scale data pipelines, orchestration, and integrations. Drive IaC strategy (Terraform), third-party API and AI/LLM tool integrations, build export pipelines and internal tooling, mentor engineers, and align cross-team technical strategy for reliable, scalable data infrastructure.

The Enterprise Data Architect will design and govern data architecture, create enterprise data models, and ensure data consistency across various systems.

Lead CX analytics strategy and operations by standardizing metrics, enabling self-service analytics, and embedding AI in the analytics lifecycle to enhance decision-making processes.

Lead end-to-end COGS and gross margin analysis for hardware and software products, model cost-saving scenarios, answer ambiguous executive questions, partner with data engineering/finance/product, build reliable datasets and analytical frameworks, and present recommendations to C-suite stakeholders.

Lead and manage a team of data engineers to develop and maintain data pipelines and warehouses, ensuring data quality and adherence to best practices.

Oversee data ingestion and transformation, manage finance data sources, ensure scalability and reliability of data platforms, and collaborate with stakeholders to align data engineering with organizational goals.