I will optimize your snowflake sql queries and reduce warehouse compute costs

Is your Snowflake warehouse spending more than it should? Are your dashboards slow or your data pipelines timing out?

I am a Snowflake SnowPro Advanced Architect Snowflake's highest-level data engineering certification. I've reduced pipeline runtimes by up to 75% and cut warehouse compute costs by over 80% for clients running complex workloads on Snowflake. I know exactly where Snowflake wastes credits and how to fix it fast.

What I will optimize:

Query Performance

• Rewrite slow SQL with optimised CTEs, joins, and filter pushdowns
• Eliminate redundant subqueries and cartesian products
• Fix missing or incorrect clustering key usage
• Tune Snowflake-specific features: QUALIFY, FLATTEN, LATERAL JOIN

Warehouse Efficiency

• Right-size virtual warehouses (XS XL) based on actual workload
• Configure auto-suspend and auto-resume policies to cut idle cost
• Identify and eliminate expensive full table scans
• Analyse query profiles for bottlenecks (spill to disk, remote I/O)

Data Architecture Fixes

• Review partition pruning and micro-partition efficiency
• Recommend materialised views or result caching where applicable
• Optimise Snowpipe and COPY INTO performance
• Reduce credit consumption on scheduled Task