Top Data & Analytics Jobs in Huntsville, AL

Design, build, and optimize end-to-end ETL/ELT pipelines using Python and PySpark for large structured and unstructured datasets. Ensure data quality through validation and reconciliation, troubleshoot performance issues, implement CI/CD and code review practices, and collaborate with IT and business stakeholders to translate requirements into scalable data solutions.

Lead design and implementation of data ingestion, data lake, and ETL solutions using Big Data technologies. Build performant cloud data pipelines, integrate multiple data sources, optimize query performance, enable analytics and data science teams, and lead offshore engineering teams.

Analyze customer and caregiver data to identify workflow improvements, build dashboards and visualizations, support Customer Success with QBRs and presentations, translate findings into actionable recommendations, and create scalable data processes while advising Product and Engineering.

Design, build, and lead a scalable, configuration-driven data integration platform. Improve performance, automate monitoring and deployments, provide escalated support, and collaborate across product and engineering to deliver reliable, secure data integrations.

Build and maintain production-grade data pipelines and ELT processes using Python, SQL, Airflow, and dbt within AWS. Design optimized schemas in PostgreSQL and Redshift, leverage AI/LLMs to improve development, automation, testing, and data quality, and scale infrastructure for large healthcare datasets.

Lead growth analytics for acquisition and activation funnels: measure channel performance, build data models and KPI reporting, run experiment analysis, and translate insights into business recommendations. Partner with Growth product team and leadership to visualize results and drive strategy.

Lead architecture, implementation, and optimization of scalable data platforms, ETL/ELT pipelines, and data governance. Ensure security and compliance, mentor junior engineers, drive CI/CD and IaC for data workflows, and collaborate with stakeholders to deliver actionable analytics and reporting.

Lead global data governance strategy and operating model, establish enterprise data management/MDM and data certification practices, build and lead the global governance function and steward program, drive change management and adoption across business lines, partner with cross-functional teams to resolve data risks and embed governance into workflows, and deliver measurable outcomes against the governance roadmap.

Senior technical leader responsible for designing and implementing scalable Databricks/Azure data architectures, building high-scale pipelines, embedding across teams to unblock delivery, mentoring engineers, and defining engineering standards and best practices for enterprise data platforms.

Lead enterprise sales forecasting, pipeline governance, and KPI reporting to drive growth performance. Own forecast reviews, executive reporting, sales compensation tracking, and data-driven insights. Partner cross-functionally with Sales, Finance, Growth Ops, and Market Leaders to improve conversion, planning accuracy, and revenue outcomes, while supporting systems, data quality, analytics automation, and performance frameworks.

Design and recommend Snowflake-based analytic architectures, lead implementation work streams, advise engineering teams on data cloud migrations, mentor junior staff, support presales, and leverage AI to optimize data warehouse and lake solutions across project lifecycles.

Design and build petabyte-scale multimodal data pipelines and infrastructure (text, audio, images, video). Own and maintain systems like Spark, Ray, and vector databases, partner with pre/post-training teams to improve data recipes through experimentation, and support large-scale dataset storage and processing for AI model training.

Design and deliver executive-ready Power BI reports, dashboards and agentic experiences. Build semantic models and self-service analytics, apply DAX, Power Query and Fabric notebooks, perform data exploration with SQL/KQL, and drive AI-enabled automation. Collaborate with data engineering to influence ingestion and transformation, translate business strategy into data solutions, and ensure performance, reliability, and scalability of reporting assets.