Snowflake Consulting
Expert Snowflake consulting for semantic layer design, warehouse cost optimization, and BI migration. Senior-led engagements with defined milestones.
What this service covers
- Snowflake consulting
- Snowflake analytics
- Snowflake semantic layer
- dbt Snowflake
- Snowflake cost optimization
- data warehouse consulting
Frequently asked questions
Do you work with dbt on Snowflake?
Yes. We use dbt Core and dbt Cloud to build transformation layers on Snowflake. We also integrate with Tableau, Power BI, and Looker as the BI layer on top.
Can you help reduce our Snowflake costs?
Yes. Warehouse right-sizing and query optimization are part of every Snowflake engagement. Most clients see a 30 to 50 percent reduction in compute costs within the first 60 days.
We already have Snowflake. Do we need to start over?
No. We work with your existing Snowflake environment. We audit what you have, identify the gaps, and fix them without requiring a full rebuild.
How does Snowflake fit with our existing Tableau or Power BI setup?
Snowflake works well as the warehouse layer under Tableau or Power BI. We design the connection architecture, optimize query pushdown, and ensure live query performance meets your dashboard refresh requirements.
What does a Snowflake consultant do?
A Snowflake consultant designs the warehouse, models the data, and builds the analytics layer that sits on top of it. In practice that means account and warehouse architecture, migration off a legacy database, a dbt transformation layer, a certified semantic model, BI integration, and the cost governance that keeps compute spend under control. The person who scopes the work is the person who does it, so nothing gets lost in a handoff to a junior team.
How much does Snowflake consulting cost?
It depends on your data volume, whether a migration is in scope, and how much modeling and governance you need. We scope every engagement against fixed deliverables and milestones before any work starts, so you see the number before you commit. A tuning-and-cost engagement on an existing warehouse is quick; a full migration with a new semantic layer is a larger build, and that is where most of the value sits.
Snowflake vs Databricks, which should we use?
Snowflake is the stronger fit when your workload is SQL analytics, BI, and governed reporting that a broad team queries, because the warehouse is simpler to run and cheaper to operate for that pattern. Databricks pulls ahead when your center of gravity is data science, machine learning, and large-scale Spark processing on unstructured data. Plenty of stacks run both. We are vendor-neutral and recommend the platform that fits your workload and your team, not the one we would rather sell.
Can you reduce our Snowflake compute bill?
Yes, and it is part of every engagement. Most overspend comes from oversized warehouses with no auto-suspend, uncoordinated queries from multiple teams, and models that rescan the same data repeatedly. We right-size warehouses, set auto-suspend and resource monitors, add clustering where it earns its keep, and rewrite the queries that cost the most. Most clients see a 30 to 50 percent reduction in compute cost within the first 60 days.
Request the 30-day Analytics Truth Audit to scope this engagement for your environment.