Design, build, and optimize scalable data pipelines and data models.
Manage and administer Snowflake environments, including virtual warehouses, secure shares, clustering, tagging, masking, dynamic tables, and performance tuning.
Ensure cost efficiency in Snowflake workloads through monitoring and optimization techniques.
Implement and maintain data governance, data quality checks, and metadata standards.
Collaborate with cross-functional teams to understand data needs and deliver robust solutions.
Develop automated scripts and transformations using Python for data processing.
Leverage AI-assisted tools (GitHub Copilot, Claude Code) to improve design, coding, documentation, and reviews.
Monitor system health, performance, and data reliability using industry tools and best practices.
Contribute to architectural discussions, documentation, and design specifications.
Use Git effectively for branching strategies, code reviews, and version control.
Support production environments and troubleshoot performance, quality, and pipeline issues.
Requirements
6+ years of experience as a Data Engineer, Software Developer, or Administrator focused on data modeling, governance, and platform administration.
3+ years of hands-on Snowflake experience including virtual warehouse management, clustering, secure shares, cost control, tagging, masking, dynamic tables, and performance optimization.
Expert-level SQL capability for analytics and database engineering.
Intermediate Python skills for data pipelines and automation.
Experience using AI-assisted code tools (GitHub Copilot, Claude Code).
Strong experience across MSSQL, PostgreSQL, OLAP/OLTP systems.
Familiarity with ETL/ELT tools, schema design for high-volume systems, and data health monitoring.
Experience implementing data governance principles and standards.
Solid understanding of cloud design principles (SaaS, PaaS, IaaS).
