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ServicesData engineering

Data engineering

Data Engineering Services

AI and analytics are only as good as the data underneath. ResoluteX builds the pipelines, warehouse models and quality checks that turn scattered operational data into something your team and your AI systems can trust — in your own cloud.

One trusted version of your data, refreshed automatically and checked before anyone relies on it.

Where this work fits

01

Pipelines

Move data from product, CRM, billing and support systems into one place on a schedule.

02

Warehouse modelling

Clean, documented tables that analysts and AI can use without guessing.

03

Data quality

Checks that fail loudly when data is late, missing or wrong.

04

AI-ready data

Prepare documents and records for retrieval and agents, with permissions intact.

What you receive

  • 01Pipelines and schedules defined as code in your repository
  • 02Warehouse models with documentation
  • 03Data quality checks and alerts
  • 04Dashboards for the agreed metrics
  • 05Runbooks and a handover

How delivery works

  1. 01

    Agree the questions

    Start from the decisions the data must support.

  2. 02

    Map the sources

    Find where each number lives and who owns it.

  3. 03

    Build and test

    Pipelines with quality checks, reconciled against the source systems.

  4. 04

    Hand over

    Documentation and alerts so your team can run it.

A good fit when

  • Every report starts with an export and a spreadsheet
  • Teams disagree about basic numbers
  • You want AI on your data but the data isn't ready

Probably not the right fit when

  • You need a vendor to operate a large data team indefinitely
  • Data volumes and sources are tiny and a spreadsheet suffices
  • No one can grant access to the source systems

Questions buyers ask

Before you scope the work

How much do data engineering services cost?

Fixed sprints start at $2.9k and run two to four weeks, depending on the number of sources and models.

Which data platforms do you use?

We build in your own cloud and warehouse; the specific platform is confirmed in the scope.

Can this feed our AI projects?

Yes — clean, permissioned data is the foundation for RAG and agents, and both sit in the same practice.

Who owns the pipelines?

You do. They are code in your repository and run in your cloud.

Related services

AI agent development
RAG development
Generative AI development

Describe the outcome in one sentence. We will return a fixed sprint plan within one business day.

Scope a sprint