Data Engineering · Warehouses · Dashboards · Automation

We build the data plumbing your business runs on.

Pipelines, warehouses, and dashboards for companies that have outgrown spreadsheets. Scoped in a day, shipped in weeks, documented so you own every line of it.

Fixed scope & price up front You keep the repo, docs & runbook
nightly_pipeline — 06:00 EST
$ dataverge run nightly_pipeline
 extract   shopify_orders      12,408 rows    4.2s
 extract   stripe_payouts       1,932 rows    1.8s
 extract   hubspot_contacts     8,110 rows    3.1s
 load      warehouse.raw            —         2.4s
 dbt run   41 models · 217 tests passed      68.0s
 refresh   6 dashboards                       3.1s

Done in 1m 23s — data current as of 06:00
Alert routing: Slack #data-alerts · 0 incidents, 34 days

An actual morning for our clients: numbers ready before the first coffee, and an alert to us — not to you — if anything breaks.

Live demo — click around

This is what we ship. Try it.

A working example of the kind of operations dashboard our clients open every morning. Sample data, real interactions — switch the date range, hover the charts.

Sample data — your dashboard uses your numbers

Revenue by day

Revenue by channel

Pipeline health — what keeps the numbers above trustworthy

JobSourceScheduleLast runRows syncedStatus
Under the hood

How we'd actually build it — no hand-waving.

Every proposal we send includes an architecture like this, with named tools and the monthly infrastructure bill estimated line by line. Here's the reference build for a company with 5–15 data sources:

01

Extract & load

Airbyte · Fivetran · custom Python

Incremental syncs from your CRM, billing, e-commerce, and ops tools. Change-data-capture where the source supports it, so we never re-pull what hasn't changed. Retries and alerting built in from day one.

02

Warehouse

PostgreSQL · BigQuery · Snowflake

Sized to your data, not to a vendor's sales target. Under ~500 GB, a managed Postgres or on-demand BigQuery usually costs $50–200/month — and we'll tell you when you genuinely need more.

03

Transform & test

dbt · SQL · Git

Version-controlled SQL models with tests on every key column — uniqueness, freshness, referential integrity. When a source changes its schema, the tests catch it before your reports lie to you.

04

Orchestrate & monitor

Dagster · Airflow · cron + alerts

Scheduled runs with failure alerts to Slack or email — routed to us, not you. Every run logged: what synced, how many rows, how long it took. Small stacks get simple schedulers, not a Kubernetes cluster.

05

Dashboards

Metabase · Power BI · Looker Studio

Metabase is free and self-hosted; Power BI is ~$10/user; we'll match whatever your team already pays for. Row-level permissions so sales sees sales and finance sees everything.

Total infrastructure bill for this reference stack: roughly $100–500/month, itemized in your quote before you commit. If a $50/month Postgres instance solves your problem, that's what we'll quote — the expensive stack has to earn its place.
Ways to work with us

Start small. Scale when it's working.

Quick win

Automate one thing

1–3 weeks · fixed price

One pipeline, one automated report, or one integration. The lowest-risk way to see how we work.

  • Single deliverable, quoted up front
  • Git repo, docs & runbook included
  • 30 days of fixes after handover
Ongoing

Your data team, on demand

Monthly retainer

Senior data engineering capacity every month — new pipelines, new dashboards, and support without a full-time hire.

  • Predictable monthly cost
  • Same-day response on breakages
  • Pause or stop any month
What we won't sell you
  • A data lake for 20 GB of data
  • A Spark cluster your workload will never need
  • Dashboards nobody asked for and nobody will open
  • A platform only we know how to operate — everything is documented and yours
FAQ

Straight answers to the usual questions.

What does DataVerge do?

We're a data engineering consultancy based in Kitchener, Ontario, working with clients across Canada, the US, and the UK. We build data pipelines, data warehouses, dashboards, and workflow automation as fixed-scope projects — from a single automated report to a complete modern data platform.

How long does a typical project take?

Most first engagements deliver working results in 2–6 weeks. A single pipeline or automated report ships in 1–3 weeks; a full warehouse-plus-dashboards build usually runs 4–8 weeks, delivered in weekly milestones with a demo every Friday.

How much does a data project cost?

Every project gets a fixed-scope quote before work starts — no surprise invoices. Tell us your goal and we respond within 24 hours with scope, timeline, and price. Ongoing infrastructure for a typical build runs $50–$500/month depending on data volume, and we itemize that number in the quote too.

Do we need a data team to work with you?

No. Many clients have no dedicated data staff — we act as their data team, and everything we build is handed over with documentation and a runbook so you own it fully. If you do have engineers, we work alongside them and transfer knowledge as we go.

What tools and platforms do you work with?

AWS, Azure, and Google Cloud; PostgreSQL, BigQuery, Snowflake, and Databricks; dbt, Airflow, Dagster, and Airbyte; Power BI, Metabase, Looker Studio, and Tableau. We fit your existing stack or recommend the simplest stack that meets your needs — if a $50/month Postgres instance solves it, that's what we quote.

Do you work remotely?

Yes — we're headquartered in Kitchener, Ontario, and work remotely with companies across North America and the UK, with overlap across all North American time zones.

Describe the problem. Get an architecture and a price in 24 hours.

No discovery-phase invoices, no slideware — a concrete plan you can say yes or no to.