Data Engineering & Business Intelligence

You have the data. You just can't get to it.

Your company generates data constantly — sales transactions, user behaviour, operational metrics, marketing campaigns. But it's scattered across a dozen tools, formatted differently in each one, and nobody trusts the numbers enough to make decisions from them. We fix that.

Discuss Your Data Needs

Data warehousing

One place for all your data, structured for fast queries

ETL pipelines

Automated data flows from every source to your warehouse

BI dashboards

Reports your team checks every morning, not ones they ignore

Real-time capable

Streaming data pipelines for when batch processing isn't enough

The Problem

Your company is data-rich and insight-poor.

Every department has their own version of the truth. Sales reports numbers from the CRM. Finance pulls from the ERP. Marketing has Google Analytics data that doesn’t match what product is seeing. When the CEO asks a straightforward question — “what was our revenue by channel last quarter?” — three people give three different answers because they pulled from three different sources with three different definitions of “revenue.”

Someone built a dashboard once. It was accurate for about two weeks. Then a data source changed its API, a new product category was added that didn’t fit the existing logic, and the person who built it left the company. Now the dashboard exists but nobody trusts it.

You’ve probably considered hiring a data analyst or data scientist. But without reliable data infrastructure underneath, their work is 80% data cleaning and 20% actual analysis. They spend their days wrangling CSVs and writing SQL against production databases instead of doing the work you hired them for.

The missing piece is data engineering — the infrastructure that collects data from your various sources, transforms it into a consistent format, stores it in a queryable warehouse, and keeps it fresh. That’s what we build. Once the plumbing works, the dashboards, reports, and analytics become dramatically easier and more trustworthy.

What We Deliver

Data infrastructure that makes your numbers trustworthy.

From extracting raw data to presenting finished dashboards — the full pipeline.

ETL / ELT Pipelines

Automated data extraction from CRMs, ERPs, databases, APIs, spreadsheets, and third-party platforms. Transformation logic that cleans, standardises, and enriches data before loading into your warehouse.

Data Warehouse Design

Snowflake, BigQuery, Redshift, or PostgreSQL warehouse architectures. Schema design, partitioning strategies, and query optimisation that make your data fast to access and cheap to store.

BI Dashboards & Reports

Interactive dashboards in Power BI, Tableau, Metabase, or custom-built analytics interfaces. Reports designed around the decisions your team actually makes — not generic charts nobody looks at.

Real-Time Streaming

Kafka, Flink, and cloud-native streaming for use cases that genuinely need real-time data — live operational dashboards, alerting systems, and event-driven architectures.

Data Quality & Governance

Data validation rules, lineage tracking, access controls, and documentation. Making sure your data stays accurate, consistent, and compliant as your organisation grows.

Source Integration

Connecting every data source your business uses — Salesforce, HubSpot, Shopify, Google Analytics, payment gateways, custom databases, and internal APIs — into a unified data layer.

Tech Stack

Data engineering tools we work with

Modern data stack components — chosen based on your scale, budget, and team capabilities.

Warehouses

Snowflake

BI BigQuery

RE Redshift

PostgreSQL

Databricks

Pipeline & Orchestration

Apache Airflow

DBT dbt

Kafka

Python

Apache Spark

BI & Visualisation

BI Power BI

TB Tableau

ME Metabase

LO Looker

SU Superset

Cloud

AWS

Google Cloud

Azure

Who This Is For

Companies that need data infrastructure

If your team spends more time finding and cleaning data than analysing it — this service is for you.

Growing Companies

Businesses past the startup stage that have accumulated data across multiple tools and need a coherent way to access, analyse, and report on it.

Data-Driven Teams

Organisations that have committed to data-driven decisions but lack the engineering infrastructure to actually deliver reliable data to decision-makers.

CFOs & Finance Teams

Finance teams tired of manual report assembly, spreadsheet reconciliation, and conflicting numbers from different departments.

E-Commerce & SaaS

Product and marketing teams needing cohort analysis, funnel metrics, LTV calculations, and attribution reporting from unified data.

Teams Preparing for AI

Companies that want to use machine learning but first need clean, structured, accessible data to train models on.

Teams Replacing Manual Reports

Organisations where someone spends hours each week pulling data, formatting it in Excel, and emailing it — and wants that automated.

FAQs

Common questions about data engineering

What clients ask before starting a data project.

What is data engineering and how is it different from data science?

Data engineering builds the infrastructure — pipelines, warehouses, and APIs. Data science analyses the data. You need engineering first. Without reliable infrastructure, data science efforts fail because the data is dirty, late, or missing.

Which BI tools do you work with?

Power BI, Tableau, Metabase, Looker, and custom-built analytics interfaces. The choice depends on your team's familiarity, licensing budget, and reporting complexity.

Can you work with our existing data warehouse?

Yes — Snowflake, BigQuery, Redshift, Databricks, PostgreSQL, and SQL Server. Whether you need to optimise queries, add data sources, or build reporting layers on top of what exists.

How long does a typical data engineering project take?

A focused pipeline or dashboard: four to eight weeks. A full warehouse build with multiple integrations: three to six months. We scope in phases so you see value early.

Can you consolidate data from multiple sources?

That's one of the most common things we do. CRM, ERP, web analytics, product databases, third-party APIs — we build pipelines that bring everything into one warehouse for consistent querying and reporting.

Do you build real-time analytics or just batch?

Both. Most reporting works with hourly or daily refreshes. For genuinely real-time needs — live dashboards, alerting, operational monitoring — we build streaming pipelines with Kafka, Flink, or cloud-native services.