Snowflake Implementation & Data Cloud

Most enterprise migrations run 3 to 6 months from kickoff to cutover, and a single-source warehouse swap can land in weeks. The long pole is rarely Snowflake itself; it is untangling the pipelines and reports that grew around the old system. We run old and new in parallel until the numbers match, then cut over.

Compute, not storage. Snowflake bills per second of warehouse runtime, so cost comes from how queries are written and how warehouses are sized and suspended. We set resource monitors, auto-suspend, and right-sized warehouses on day one, and most teams watch the bill drop once we tune the heavy queries.

No. We migrate by domain, usually starting with the workloads that cost the most to run or hurt the most today. Each domain gets validated against the source before anyone trusts it. Big-bang cutovers are how you end up reconciling numbers at 2am.

Role-based access, row and column security, masking policies for PII, and object tagging for lineage and cost attribution. We wire this in as we migrate, not as a cleanup project afterward.

A data owner who can settle what the numbers should be, and access to the source systems. We bring the architects and engineers. The work that stalls migrations is usually decisions, not code.