Senior Director, Data and Analytics

Requisition Number: 26987 

When you work for AmeriGas, you become a part of something BIG! Founded in 1959, AmeriGas is the nation’s premier propane company, serving over 1.5 million residential, commercial, industrial and motor fuel propane customers. Together, over 6,500 dedicated professionals will deliver over 1 billion gallons of propane from 1,800+ distribution points across the United States.

 

 

Job Summary (Purpose)

The Sr Director of Data & Analytics serves as both the strategic business leader and technical expert for the AmeriGas data organization, providing comprehensive leadership across all data science, engineering, and business intelligence/analytics initiatives. Working in collaboration with the IT organization, this role sits within the functional business and combines technical expertise with business acumen to drive organizational transformation through data-driven decision making. The position requires the ability to lead high-performing teams of data professionals, manage stakeholder relationships across all organizational levels, and serve as the primary champion for data initiatives in AmeriGas. Critical to this role's success is stakeholder engagement and stakeholder education to ensure data tools meet overall business objectives, are adopted by users, and continually improved based on feedback.

 

Major Responsibilities

Strategic Leadership & Business Partnership

• Develop and execute comprehensive technical and business strategy for all data science, data engineering, and business intelligence initiatives

• Serve as the primary liaison between the data organization and senior leadership, translating business/stakeholder objectives into data requirements and technical solutions

• Represent the data organization in enterprise-wide UGI initiatives, providing thought leadership on data capabilities and strategic opportunities

• Manage vendor relationships and external partnerships to support organizational objectives

•Lead organizational change initiatives related to data adoption, education, and process automation

• Establish comprehensive data governance framework including security, compliance, and technical standards; implement data stewardship and ownership structures with business partners; and develop automated governance platforms to address infrastructure gaps in collaboration with IT teams

• Data Engineering & Infrastructure Leadership

• Design and implement enterprise data architecture including the creation, expansion, and governance of an AmeriGas data store/mart. Using a medallion architecture, this data repository is to be the standardized, governed, and cleaned dataset upon which all data science, business intelligence, and generative AI solutions within AmeriGas are built upon

• Lead integration initiatives that connect disparate data sources into the standardized platform

• Design and implement scalable data pipelines and ETL processes using modern cloud platforms (Databricks, Snowflake)

• Oversee data quality monitoring, testing, and validation frameworks that ensure reliable data products

• Manage cloud infrastructure optimization, cost control, and performance monitoring

 

Data Science Leadership

• Direct the development, deployment, and maintenance of critical statistical and machine learning models including but not limited to: demand forecasting, customer churn prediction, and gross margin measurement, forecasting, and optimization

• Ensure statistical rigor and scientific methodology in all analytical work, with focus on interpretability and business applicability

• Guide organizational discussions on generative AI strategy and provide technical input on AI solution selection, while leveraging these technologies to develop and deploy generative AI tools and applications built on the AmeriGas data mart

 

Business Intelligence and Project Management

• In collaboration with the business and stakeholders, direct the development, deployment, and maintenance of business intelligence tools/apps that disseminate otherwise hard to interpret data and insights into easy to digest and manipulate dashboards

• Oversee the planning, execution, and delivery of all data project initiatives (Data Engineering → Data Science → Business Intelligence), ensuring projects are completed on time, within budget, and to business/stakeholder requirem