Services › Data engineering

Data pipelines that refresh on time, every time

We move data from your CRM, ERP, POS and APIs into one place, transform it with tested models, and tell you when something breaks.

PythondbtFivetranAirbyteAWS GlueSQL
Sound familiar?

Problems we fix

Reports depend on manual exports
Pipelines fail silently overnight
The same logic is rebuilt in every dashboard
A new source takes weeks to add
Nobody knows where a number came from
Costs grow with every new connector
Data engineering and ETL

What we do

01

Source integration

Connectors and custom Python for CRMs, ERPs, POS systems and APIs.

02

Transformations with dbt

Tested, documented models with clear lineage.

03

Scheduling and orchestration

Jobs that run in order and retry when they should.

04

Monitoring and alerts

Checks for freshness and volume so failures are caught early.

05

Cost review

Right-size connectors and compute so you stop paying for idle syncs.

06

Hand-off and docs

Runbooks your team can follow without us.

How we work

Four steps, no surprises

Discover

A free call to understand your goals, data and tools. You get a written scope and a fixed price.

Design

We agree on metrics and layouts with you before building, so there are no surprises.

Build

Regular updates and working previews, with revisions before sign-off.

Hand off

Documentation and a walkthrough so your team can own what we built.

Results

Recent work and client reviews

Client names are kept private.

Workforce scheduling

Staffing and utilization analytics built on a cloud warehouse with a self-serve dashboard.

BigQueryLooker StudioETL
Finance and sales

Financial and sales dashboards on Microsoft Dynamics 365 data and Fabric models.

Power BIDynamics 365Fabric
★★★★★
The team built out a full flow for us from CSV files to Google Sheets to BigQuery to a Looker dashboard. Work was done efficiently and well. Project completed successfully, and we are satisfied with the results.
Dashboard development from CSV filesVerified client review · BigQuery · Looker
★★★★★
Streamlined our reporting end to end, from pipeline to dashboard. Clarity, speed, and technical depth made the whole thing easy.
End-to-end reportingVerified client review · ETL · Dashboards
FAQ

Data engineering and ETL questions

Which tools do you use for pipelines?

Python, dbt, Fivetran, Airbyte and AWS Glue, chosen by your sources, budget and team. We do not push one stack.

Can you connect to our POS or ERP?

Usually. We use a standard connector where one exists and custom Python against the API where it does not.

How do you catch pipeline failures?

We add freshness and row-count checks with alerts, so a failed job shows up before someone opens a report.

Do we need a data warehouse first?

Not always. For small projects we can load into a database you already have. For growing data we recommend a warehouse.

How long does a pipeline project take?

Adding a few sources with tested models often takes 2 to 4 weeks. These are estimates; we confirm after a call.

Will our team be able to maintain it?

Yes. We document every pipeline and walk your team through it at hand-off.

Talk to us about data engineering and ETL

A free consultation. You get a written scope and a fixed price before any work starts.

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