What are the responsibilities and job description for the Lead Snowflake Data Engineer position at Upward Talent?
Our client is seeking a Lead Snowflake Data Engineer to design, own, and deliver end-to-end data engineering solutions in modern cloud environments. This role requires full lifecycle ownership across Snowflake pipelines, data modeling, and performance optimization, with exposure to Cortex AI and advanced analytics use cases.
Responsibilities & Qualifications
Requirements
Responsibilities & Qualifications
- Lead design and development of end-to-end ELT pipelines in Snowflake
- Architect scalable, high-performance data models for analytics consumption
- Build backend data services using Python and PySpark
- Drive performance tuning (query optimization, clustering, warehouse scaling)
- Leverage Snowflake Cortex AI or similar for advanced data capabilities
- Enforce data governance, security, and compliance best practices
- Collaborate across business, analytics, and engineering teams
- Provide technical leadership and mentorship
- Communicate architecture decisions in client-facing environments
Requirements
- 10 years of experience in data engineering or equivalent ownership of production systems
- Deep expertise in Snowflake (data modeling, performance tuning, optimization)
- Strong experience with Python, PySpark, and advanced SQL
- Proven ownership of end-to-end data pipelines (ingestion transformation consumption)
- Experience designing modern data warehouse architectures (ELT, dimensional modeling)
- Strong understanding of distributed data processing and large-scale systems
- Experience with Snowflake Cortex AI or similar AI-driven capabilities preferred
- Ability to explain and defend architecture decisions and trade-offs