Hours back every week
Automated loads replace the exports, copy-pastes, and spreadsheet merges your team does by hand today.
Data warehousing & pipelines
“Our data lives in a dozen apps, and the syncs between them keep breaking.”
Your CRM, billing system, ad platforms, and databases each hold part of the picture. I build the warehouse that brings them together and the pipelines that keep it current, without anyone exporting a file.
Book a free consultationWhat it's worth to your business
Current data, on schedule
Incremental syncs mean reports reflect this morning's activity, not whenever someone last ran an export.
Failures caught early
Monitoring flags a late or broken sync before it shows up in a dashboard or a customer conversation.
Signs you need this
- Someone spends Monday mornings exporting and merging files
- Reports run directly against your production database
- A sync broke and nobody noticed for days
- A new tool takes weeks to show up next to everything else
What's included
Warehouse setup
Snowflake, BigQuery, Databricks, or Postgres, chosen for your size and budget, with separate development and production environments.
Managed connectors
Fivetran or Airbyte for common sources like Salesforce, HubSpot, Stripe, and Google Ads, configured to load only what changed.
Custom pipelines
Python pipelines for internal systems, APIs, and files that no off-the-shelf connector covers.
Orchestration
Every load scheduled and sequenced, so downstream work runs only after fresh data lands.
Monitoring and alerts
Freshness and volume checks that alert you in Slack or email when something is off.
Common questions
Fivetran, Airbyte, or custom pipelines?
Usually a mix. Managed connectors are quickest for popular SaaS tools, and custom code is often cheaper for high-volume or unusual sources. I recommend based on your sources and budget.
Which warehouse is right for us?
It depends on how much data you have, how often it's queried, and who maintains it. Snowflake is cost-efficient because you pay for compute only while it runs, and it scales as you grow. For a small, steady workload, a database like Postgres can be simpler to run. I'll recommend the fit for your business. I wrote more about this in Your Data Warehouse Doesn't Have to be a Fancy Next-Gen Tool.
Who keeps it running after it's built?
You get alerts whenever data is late or missing, and every pipeline is documented so your team knows how it works. I can stay on to maintain it, or hand it over to your team.