Lead Data Engineer

Amerigas•Kng Of Prussa, PA

About The Position

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. Position Summary The Lead Data Engineer is a hands-on technical leader responsible for leading data engineering initiatives, managing a team of 1-3 direct reports, and personally building robust data models and ETL pipelines to meet organizational goals. This role requires proficiency in Snowflake, SQL, and Databricks, with extensive experience integrating data from multiple source systems. The Lead Data Engineer will be deeply involved in coding and implementation work while also serving as a thought leader in best data engineering practices, mentoring team members, and establishing technical standards across the organization.

Requirements

Proficiency in Snowflake, including advanced features such as data sharing, streams, tasks, and performance optimization
Expert-level SQL skills for complex queries, stored procedures, and database optimization with ability to write highly efficient, production-ready code
Extensive hands-on experience with Databricks, including Delta Lake, Apache Spark, and cluster management
Proven experience designing and personally implementing ETL/ELT processes from multiple heterogeneous source systems
Advanced working knowledge of Python and/or other programming languages for data engineering workflows
Strong understanding of modern data architecture principles, including data warehousing, data lakes, and lakehouse architectures
Excellent communication skills with ability to effectively convey complex technical concepts to both technical and non-technical stakeholders
Business acumen with ability to identify risks, opportunities, and generate innovative solutions to complex data challenges
Strong project management skills with ability to prioritize competing demands and deliver results on time
Collaborative mindset with experience working across data science, analytics, engineering, and business teams
Bachelor's degree in Computer Science, Data Engineering, Information Systems, Mathematics, Statistics, or related technical discipline required; Master's Degree preferred
5+ years of hands-on, individual contributor experience in data engineering with progressively increasing responsibility
2+ years of experience in a technical leadership or team lead capacity while maintaining significant hands-on coding responsibilities

Nice To Haves

Experience with QlikSense and QlikView for data integration and analytics (strongly preferred)

Responsibilities

Personally design, build, and maintain complex ETL/ELT pipelines from diverse source systems using Snowflake and Databricks
Write production-quality code and SQL on a daily basis, serving as a primary technical contributor to critical data engineering projects
Lead and manage a team of 1-3 data engineers, providing technical guidance, code reviews, mentorship, and performance management
Architect and implement scalable data models and infrastructure that align with business objectives
Drive innovation and establish best practices in data engineering, serving as the subject matter expert for modern data platform capabilities
Manage the full life-cycle development process for data engineering projects, from requirements gathering through deployment and maintenance
Collaborate with data science and BI teams to enable deployment of scalable data solutions across the company's ecosystem
Establish and enforce data engineering best practices, coding standards, and quality assurance protocols through both leadership and example
Provide expert-level support and hands-on troubleshooting for SQL optimization, data warehousing, and cloud data platform architecture
Adhere to stringent quality assurance and documentation standards using version control and code repositories (e.g., Git, GitHub)