Requisition Number: 28409

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.

Duties and Responsibilities

Hands-on development:
• Personally design, build, and maintain complex ETL/ELT pipelines from diverse source systems using Snowflake and Databricks
Direct technical contribution:
• 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
Thought leadership:
• 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)

Knowledge, Skills and Abilities

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

Minimum Qualifications

• 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

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