Snowflake Migration, Warehousing & Optimization

I need an experienced Snowflake specialist to take ownership of three key pieces of work on my current analytics initiative.

First, you will migrate our existing data—currently split between several relational SQL databases and a large collection of flat CSV files—into Snowflake. You’ll design and automate repeatable ingestion pipelines, handle any necessary data cleansing, and validate row-level accuracy once the data lands in its new home.

Second, once the data is in place, you’ll convert that raw load into a well-structured, scalable Snowflake data warehouse. Proper schema design, thoughtful use of micro-partitioning, and clear naming conventions are crucial, as downstream analysts will rely on your work for daily reporting.

Finally, performance matters. I need our most heavily used queries reviewed, rewritten where appropriate, and tuned to take full advantage of Snowflake’s caching, clustering, and warehouse-sizing features so that dashboards refresh quickly and ad-hoc analysis runs smoothly.

Deliverables I expect:
• Automated load scripts (or Snowpipe/TASKS configurations) for the SQL and CSV sources
• A documented warehouse schema with DDL ready to run in any environment
• A set of optimized, benchmarked queries (before/after metrics included)
• Clear hand-off documentation so future maintainers understand the build

If you have a proven track record with Snowflake migrations, warehouse architecture, and query tuning, I’d love to hear how you would approach each stage and the timeline you foresee.