DATA ENGINEERING
Data engineering services for data you can rely on
Our data engineering services build the pipelines, warehouses and data models behind your reports and AI. Data arrives on time, passes tests on the way in, and carries clear ownership and lineage.
Data Readiness
- Source inventory with quality scores and owners
- Target architecture and platform recommendation
- Phased pipeline plan with the first build scoped
WHY IT MATTERS
Cloud data engineering with tests at every step
Broken pipelines usually fail quietly: a missed load, a renamed column, a duplicated feed. We build pipelines that check themselves, alert the right person and document what each table means.
CAPABILITIES
What our data engineering services deliver
Data pipeline development
Batch and streaming pipelines from CRMs, ERPs, databases, files and APIs, scheduled, retried and monitored so nothing fails silently.
Warehouse and lakehouse design
Through data warehouse consulting, we design Snowflake, BigQuery, Redshift or Databricks setups sized to your volumes and your team's skills.
Data modelling with dbt
Clean, documented models with tests for freshness, uniqueness and relationships, so analysts build on tables they understand.
Unstructured data processing
Emails, PDFs and scanned documents turned into structured tables, with PRISM-QC review for fields that need a human check.
Data quality monitoring
Automated checks and alerts catch late, missing or unusual data before it reaches a dashboard, a report or a model.
Governance and access
Row and column level security, lineage and a searchable catalogue, so people find the right data and see only what they should.
USE CASES
Pipelines we build
ERP and Tally consolidation
A multi-entity manufacturer brings ledgers, inventory and sales from several systems into one warehouse with daily refreshes.
Customer 360 for SaaS
Product usage, billing and CRM records joined on one customer key, ready for churn analysis and quarterly account reviews.
Matter data for law firms
Matter files, time entries and invoices extracted into tables, so partners can see work in progress by client and by matter.
Features for machine learning
Versioned, tested features for forecasting and scoring models, served the same way in training and in production.
HOW WE DELIVER
Five gates. You sign each one.
Every Data Engineering engagement runs on PRISM OS. Nothing moves to the next phase until you approve the evidence.
Plan
Agree the tables, freshness and owners the business needs
You sign: Problem BriefResearch
Profile sources, volumes, schemas and change patterns
You sign: Frozen PRD-LiteImplement
Build first pipelines and models with tests
You sign: Working prototype + eval reportStabilise
Add monitoring, alerts, lineage and access controls
You sign: 3-click UAT sign-offMaintain
Tune costs, handle schema changes and add sources
You sign: IP handover + warrantyData Readiness
A fixed-scope first step. You keep everything it produces, whether or not you build with us.
- Source inventory with quality scores and owners
- Target architecture and platform recommendation
- Phased pipeline plan with the first build scoped
WHY SMARTX
Why SmartX for Data Engineering
Tested like software
Pipelines live in version control with code review, automated tests and CI, so changes ship safely and can be rolled back.
Costs kept visible
We tag and track warehouse spend by team and job, so a runaway query shows up long before the monthly invoice does.
Messy sources welcome
Legacy ERPs, Tally exports, shared drives and inboxes are common starting points. We build connectors where none exist yet.
Platform-neutral advice
Our Databricks consulting services sit alongside Snowflake and BigQuery work, so we recommend the platform that fits your data and team.
TOOLS WE USE
The stack, chosen per problem
ENGAGEMENT MODELS
Choose how we work together
Every model keeps the same signed gates, fixed milestones and full code ownership.
Gated delivery pod
A senior pod owns the outcome from Problem Brief to production, priced per gate so you can stop at any signature.
Dedicated engineers
Engineers who join your team and sprints, with PRISM briefs and evidence reviews added on top of your process.
PRISM OPS retainer
Hosting, security and a monthly improvement budget, run by the same engineers who built the system.
SELECTED WORK
Evidence, not promises.
Business workflow automation for a rapid construction business
We documented how work really flowed, worked through the unclear cases with the team and automated the process at pace.
Now growing through deeper customer engagement.
Read the case study“SmartX is our technology partner for business workflow automation of our rapid construction business. We found the SmartX team to be extremely diligent and thorough in working through ambiguous situations, documenting the process flows and implementing the solution at a fast pace.”
FAQ
Questions before you book
Not covered here? Ask on the call.
Do we need a data warehouse or a lakehouse?
A warehouse suits mostly structured data and SQL reporting. A lakehouse suits large volumes, raw files and machine learning workloads. Smaller teams often need only a warehouse at first, and we design so lake storage can be added later.
Can you take over pipelines another team built?
Yes. We audit existing jobs, add tests and monitoring, document what each one does, and fix the fragile ones first. You get a stable baseline before any new work starts on top of it.
How do you handle sensitive data?
We classify sensitive fields early, mask or tokenise them outside production, and apply row and column security in the warehouse. Access is logged, and data stays in the region your policy requires.
Will our own team be able to run it?
That is the goal. Everything lives in your repositories and cloud accounts, documented and tested. We run handover sessions, and PRISM OPS can provide hosting, security and ongoing changes if you want support after launch.
START WITH CLARITY
Find the weak points in your pipelines
Book a free discovery call to review your sources, your current pipelines and the reports that depend on them.
- 1We review your context within one business day.
- 2A senior product engineer joins the call.
- 3You leave with a clear recommended next step.