Pillar 02 — Data Engineering
The foundation everything sits on.
Real-time pipelines, ETL, warehouses, and BI — built fast, tested, and understandable, whether you're moving off spreadsheets or replacing a broken warehouse.
"SimVictus turns complex operational data into smart, actionable insight in real time — decisions that took days now take minutes."
CEO — SimVictus
The problem
Dashboards everywhere. Decisions nowhere.
When data is scattered across tools and nobody trusts the numbers, reporting becomes a monthly argument instead of a daily instrument. The value isn't more charts — it's a foundation you can build on.
One coherent architecture
Ingestion, transformation, storage, and consumption designed together — not a pile of disconnected tools.
Trust at every layer
Tests, lineage, and alerting from day one, so every number in every dashboard is one you can defend.
Deliverables
What we build.
ETL / ELT Pipelines
Airflow, dbt, and Dagster — reliable, observable, tested pipelines with retry logic and lineage.
Snowflake & BigQuery
Architecture, data modelling, cost optimisation, and governance for modern cloud warehouses.
Real-time Streaming
Kafka and Flink pipelines with sub-second latency for tracking, financial events, and live dashboards.
Data Quality & Lineage
Great Expectations, dbt tests, and lineage graphs so you know where every number came from.
BI & Dashboards
Metabase, Grafana, and custom React dashboards — including GIS and real-time views, proven on SimVictus.
Data Platform Setup
End-to-end platform design for teams moving off spreadsheets into a real, coherent stack.
How we work
Four steps from brief to production.
- 01
Understand
Discovery call, scope, and a written brief.
- 02
Design
Architecture and a plan you approve before any code.
- 03
Build
Async-first delivery with weekly demos.
- 04
Hand over
Docs, walkthroughs, and 30 days of support.
Technology
The stack we reach for.
Proof
SimVictus
GIS & BI · B2B
One intelligence layer fusing GIS mapping, CCTV analytics, and business intelligence into a single real-time view — turning heterogeneous data into fast decisions.
Read the case study →FAQ
Questions, answered.
Everything you might want to know before reaching out.
We're on spreadsheets today. Is that too early for a data platform?
No — that's exactly the right time. We design an ingestion-to-consumption architecture sized to where you are, so you don't outgrow it in a year.
Cloud warehouse — Snowflake or BigQuery?
Depends on your stack, budget, and query patterns. We'll model both against your actual workload and explain the trade-offs before committing.
How do you make sure the numbers are trustworthy?
Tests and lineage are built into the pipelines, not bolted on. You can trace any figure back to its source.
Ready to fix your data stack?
Tell us what you're trying to build. We'll tell you how we'd approach it, what stack we'd choose, and what timeline looks realistic.