Analytics engineering, end to end

Advice on the stack, pipelines that hold, models your team trusts, and reporting you can run without us

What we do

Four things, in the order you usually need them

1

Advice & architecture

Which warehouse, which BI tool, how to connect A to B. We resell nothing and take no vendor commission, so the recommendation is only ever the one that fits.

  • Tool and platform selection
  • Schema and data-model design
  • Migration planning and sequencing
  • A second opinion on a stack you already have
Tool selectionSchema designMigrations
2

Pipelines & warehouse

Every source landing in your warehouse reliably, on a schedule, without anyone babysitting it.

  • Warehouse setup and cost tuning
  • Ingestion from products, ad platforms and third-party APIs
  • Scheduling, retries and failure alerting
  • Historical backfills
BigQueryPostgresAirbyteGA4Ads APIsPython
3

Analytics engineering

Tested, documented models that turn raw tables into metrics your whole team agrees on.

  • dbt or Dataform projects built from scratch, or rescued
  • Metric definitions everyone shares
  • Tests and documentation so changes are safe
  • Refactoring SQL nobody dares touch
dbtDataformSQLPython
4

Dashboards & reporting

Reporting built around the decisions you make, then handed over so you can change it yourself.

  • Executive, operational and marketing reporting
  • Self-serve models your team can extend
  • Automated delivery to inboxes and Slack
  • Handover and training, not a dependency
LookerLooker StudioPower BI

What we work with

The tools we reach for most, grouped by what they do

Warehouse & database

BigQueryPostgreSQLSQL

Transformation

dbt CloudDataformPython

BI & reporting

LookerLooker StudioPower BI

Sources & ingestion

GA4Google AdsMeta AdsAirbyteApps ScriptAPIs

This is where our work actually lives, not a list of everything on the market. If your stack is somewhere else, that is usually fine — the modelling and the thinking travel, and we will say so plainly if a job needs someone who lives in that tool every day.

Common Questions

Everything you need to know about our services

Four things: advice on which tools to pick, pipelines that land your data somewhere reliable, modelling in dbt or Dataform so everyone reads the same numbers, and reporting in Looker or Looker Studio. Most engagements start with one of those and grow into the others.

Both. We can audit and optimize your current data infrastructure, migrate to new platforms, or build from scratch. Whether you need to scale existing pipelines or implement a complete new data warehouse, we have the expertise to deliver.

It depends on scope. A dashboard build is usually 2-4 weeks, a pipeline into a warehouse 4-8 weeks, and a full modelling layer 6-12. An advisory engagement can be a single session. You get a timeline before anything starts, not after.

Our deepest experience is BigQuery, dbt and Dataform, Looker and Looker Studio, with GA4 and ad-platform data alongside. That is where most of our work has been, so that is what we name. The modelling itself travels between tools, and we will tell you plainly if a job would be better served by someone who lives in your platform every day.

Yes. We offer monitoring, maintenance, troubleshooting, and optimization on a retainer or as-needed basis. We also provide training to ensure your team can manage and extend the systems we build.

Ready to Build Your Data Infrastructure?

Schedule a free consultation to discuss your project and explore how we can help.

Schedule a Call View Case Studies