Lead Data Engineer – Snowflake

Job Description

Job title: Lead Data Engineer – Snowflake

Responsibilities:

• Lead and mentor data engineers, providing technical guidance, coaching, and oversight of engineering deliverables.
• Own day-to-day delivery of data engineering initiatives, including planning, prioritization, execution, and issue resolution.
• Partner with business and technical stakeholders to translate business requirements into clear technical designs and execution plans.
• Design, build, enhance, and maintain scalable data pipelines and transformation workflows.
• Develop and optimize data solutions using dbt, Apache Airflow, Google Cloud Platform (GCP), and Snowflake.
• Write and optimize complex SQL for data transformation, integration, and analytics use cases.
• Establish and promote software engineering best practices, including Git-based version control, CI/CD, automated testing, and code reviews.
• Monitor data pipelines, troubleshoot failures, and drive improvements in performance, reliability, and data quality.
• Coordinate project activities, dependencies, risks, and deliverables across technical and business teams.
• Ensure solutions meet established standards for scalability, maintainability, security, and performance
• Act with integrity, professionalism, and personal responsibility to uphold the firm’s respectful and courteous work environment.

Qualifications

• Bachelor’s degree in Computer Science, Information Systems, or a related field, or 4+ years of relevant Snowflake experience.
• Demonstrated experience in a Lead Data Engineer, Senior Data Engineer, or similar technical leadership role.
• Prior experience leading, mentoring, and providing technical direction to data engineering teams.
• Strong hands-on experience developing and maintaining production data pipelines using:
• dbt
• Apache Airflow
• Google Cloud Platform (GCP)
• Snowflake
• Advanced SQL skills, including experience developing and optimizing complex data transformations.
• Strong understanding of modern data engineering architectures, ETL/ELT processes, data modeling, and orchestration.
• Experience applying software engineering best practices to data engineering, including Git, CI/CD, automated testing, and code quality standards.
• Proven project management and day-to-day delivery oversight experience.
• Ability to manage competing priorities, dependencies, risks, and technical deliverables.
• Strong communication and stakeholder-management skills.
• Demonstrated ability to translate business requirements into technical execution plans, as well as explain technical concepts and constraints to non-technical stakeholders.
• Ability to balance hands-on engineering responsibilities with team leadership and delivery management.