Top Data & Analytics Jobs in Huntsville, AL

Leads marketing measurement strategy through geo holdout and incrementality testing, forecasting, experimentation, and statistical analysis. Partners with Marketing, agencies, and Data Science to guide channel budgets and campaign decisions. Queries large-scale data using SQL and Python in Databricks and BigQuery, develops measurement models, automates analyses with AI tools, and mentors analysts while providing technical leadership.

Lead pre-sales technical engagements to design and optimize scalable cloud lakehouse data platforms (Snowflake/Databricks). Provide architecture reviews, ETL/ELT pipeline design, governance and AI-ready data foundations, support services sales, and translate technical tradeoffs into actionable recommendations for engineering and executive stakeholders.

Build and maintain scalable data pipelines, infrastructure, data models, and APIs using Python, SQL, Airflow, Snowflake, dbt, Terraform, and cloud services. Ensure data quality, security, observability, and reliability while collaborating with analysts, product managers, and engineering teams. Own aspects of the FastAPI data service, including design, deployment, monitoring, and performance. Handle sensitive healthcare data in compliance with governance standards.

Lead pre-sales data engineering engagements to design and implement scalable lakehouse data platforms (Snowflake/Databricks). Advise customers on data strategy, governance, pipelines, AI-ready foundations, migrations, and translate technical solutions into business outcomes while supporting sales and partner enablement.

Build and maintain scalable ELT pipelines, dbt models, semantic layers, and governed product analytics assets. Partner with Data Engineering, Product Engineering, Data Governance, analysts, and product managers to define trusted metrics, monitor data quality, document taxonomies, and support self-service analytics. Translate product usage telemetry into certified metrics for expansion and upsell analysis, while communicating technical concepts to technical and non-technical stakeholders and driving engineering best practices.

Leads a data engineering team and supervises one Data Engineer while designing, maintaining, and optimizing reliable data pipelines and infrastructure. The role integrates internal and external data sources, supports SaaS analytics dashboards and connected platforms, improves data-store performance, and ensures infrastructure quality, security, and uptime. Requires proficiency in Python, databases, distributed processing, orchestration, AWS, and machine learning.

Leads business intelligence and database analysis to generate revenue insights, solve complex business problems, optimize digital performance, support sales and marketing initiatives, and develop predictive data products. The role requires advanced SQL analysis across large data warehouses, Tableau and web analytics reporting, data validation, executive presentations, and leadership of junior staff.

The Account Insight Manager delivers end-to-end analytics, reporting, dashboards, and data-driven insights supporting client renewals, retention, and upsell opportunities. Responsibilities include data extraction and validation, metric definition, trend and utilization analysis, report automation, executive presentations, CRM updates, cross-functional coordination, and client support. The role partners with a Consulting Account Manager, manages deadlines and risks, monitors performance guarantees, and performs administrative and data-entry duties. Travel may be required up to 25%.

Build, validate, deploy, and maintain forecasting, optimization, simulation, predictive, and cost-assessment models for digital assessment operations. Develop analytics pipelines, dashboards, and decision-support tools; improve operational efficiency, capacity planning, customer experience, and cost management. Partner with Product, Program, Operations, Technology, and Finance teams to translate analysis into decisions, shape the analytics roadmap, and identify new modeling opportunities.

Build and maintain business intelligence models, dashboards, reports, and compensation analyses for shelter, breeder, and sales channels. Support insurance regulatory reporting, ad hoc analytics, data quality, governance, automation, and performance tuning. Partner with data engineering, compliance, and business teams to improve enterprise data models and enable AI-driven initiatives.