AmeriGas
AmeriGas is a Drug Free Workplace. Candidates must be able to pass a pre-employment drug screen and a criminal background check. AmeriGas is an Equal Opportunity Employer.
Senior Director, Data and Analytics
Location: King Of Prussia, PA, US, 19406
Company: AmeriGas Propane, Inc.
Requisition Number: 26987
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 requirements
Coordinate resource allocation and priority management across multiple concurrent projects, balancing immediate needs with long-term strategic objectives
Implement structured communication protocols that keep stakeholders informed and engaged throughout project lifecycles
Drive continuous improvement in project delivery methodologies and organizational efficiency
Ensure all teams follow best practices in CI/CD / version control / documentation
Organizational Leadership & Team Development
Build and lead high-performing teams of data scientists, data engineers, systems engineers, and business intelligence professionals
Provide inspirational leadership that fosters collaboration, innovation, and continuous improvement across all data teams
Mentor and develop team members with focus on both technical excellence and business acumen, ensuring data solutions meet stakeholder needs
Establish clear performance expectations and accountability frameworks that balance technical rigor with business impact
Knowledge, Skills & Abilities
Business & Strategic Acumen
Deep understanding of business operations with ability to identify opportunities for data-driven improvements
Knowledge of budgeting, resource planning, and vendor management
Experience with project management methodologies and business process improvement
Strong analytical and problem-solving skills with ability to approach complex challenges systematically
Leadership & Communication
Strong emotional intelligence and ability to navigate organizational politics effectively
Exceptional verbal and written communication skills with demonstrated ability to engage audiences at all organizational levels
Experience managing change initiatives and driving adoption of new technologies and processes
Proven ability to translate complex technical concepts into business value and actionable insights
Technical Leadership Excellence
Knowledge of modern data engineering tools and cloud platforms (Python, Qlik, SQL, Databricks, Snowflake)
Proficiency in statistical analysis, machine learning, and predictive modeling techniques
Deep understanding of data architecture, governance, and quality management principles
Experience with, or willingness to learn, MLOps practices, model deployment, and production system management
Experience with or drive to learn modern generative AI solutions, including LLM and RAG model deployment, with understanding of underlying data requirements to optimize AmeriGas data architecture for AI utilization
Understanding
Education & Experience Requirements
Master's degree in Data Science, Computer Science, Statistics, Economics, Enginee
