DeployedWe run it in production

How LeanScale runs BigQuery

BigQuery is part of the LeanScale data and AI layer in Data Warehouse. Our teams implement, migrate and operate it inside live client environments.

Talk to the team that runs BigQuery cloud.google.com ↗

Projects we run on it: 2
Native integrations in our stack: 7
Hub documents: 3

What we build

What we build on BigQuery

2 projects from the LeanScale catalogue run on BigQuery, each with a typical timeline from our delivery record.

FinOpsBlueprint

Usage metering and billing sync

What gets counted and what gets invoiced are the same number.

2–3 weeksBilling and entitlements

Data and AI layerBlueprint

Warehouse and pipelines

CRM, billing and product data in one warehouse, modeled and tested.

4–8 weeksData pipelines

Connected

How BigQuery fits the rest of the stack

Headless readiness and native integrations, read off the vendors’ own pages. Nothing here is asserted from memory.

Connects natively with 7 partners we run

From the knowledge hub

What we’ve published on BigQuery

1 playbooks · 1 customer stories · 1 docs

Method Revenue Systems

Executive GTM Reporting

Every Executive GTM Reporting project moves through the same four phases. This is a project you win in the Blueprint — by the time you're building cha…

22 sections · 18 min read

Method GTM Tech Demos

Attio with Zev Lebowitz

Zev Lebowitz walks through Attio and its data-model-first approach to CRM, where objects and relationships are shaped to the business rather than adap…

3 sections · 44 min read

Proof CRM Architecture & Migration

Building a first real sales system for an AI company selling into enterprise

A fast-growing AI company had added a business tier and was fielding large unsolicited inbound with almost no sales infrastructure. LeanScale designed…

3 sections · 3 min read

Everything on BigQuery

Data Warehouse