Data Engineering & Ops
Analytics Engineering
Modelled, tested and documented tables in version control — the semantic layer your analysts never get the time to build.
100% delivery success — delivered worldwide across seven regions
What you get
Where Analytics Engineering earns its place
Modelled, tested, documented tables.
- A metric catalogue with named owners
- Tests on every critical table
- Documentation that stays current
Tools & platforms
What we build it with
The stack MOD actually delivers this on.
Delivery model
How the work actually runs
One delivery model, whatever the engagement. You always know what is shipping this week and what it is worth.
Discovery
We map your sources, decisions and blockers, understand the business goal, and agree what success looks like before anything is built.
Solution design
We design the architecture, data models and use cases — right-sized to your team and your cloud — and cost the work before you commit.
Development
Weekly sprints against a visible backlog: pipelines, models, dashboards and applications, all in version control and yours from day one.
Testing & validation
Every pipeline and model is tested — with frameworks like PyTest and Great Expectations — so the numbers are trustworthy before they ship.
Deployment & training
We deploy into your cloud and train the people who will run it, so the capability lands with your team, not just our code.
Support & optimisation
Observability, alerting and continuous improvement keep the system fast, accurate and cost-efficient long after go-live.
Proof
Related work
One source of truth from 50+ scattered sources
Data strategy and cloud architecture on Google Cloud, ingesting 50+ sources through Stitch, modelled in dbt and surfaced to the CEO and Head of Product in Looker Studio.
Workforce analytics for Nestlé’s supply & demand planning
HR data marts on SAP feeding automated daily ingestions through AWS Glue and Databricks, on a medallion architecture, so planners could see available resource against production targets.
FAQ
Questions buyers actually ask
Straight answers. If yours is not here, ask us on a call — we will tell you if we are the wrong fit.
Ask a questionModelled, tested and documented tables in version control, plus a semantic layer — so revenue means the same thing in finance, sales and the warehouse.
Every critical table is tested (we use PyTest and Great Expectations) and documented, with lineage from source to the figure on the slide.
Next step
Ready to find out what your data is worth?
Thirty minutes with a delivery lead, not a salesperson. You leave with a point of view on your highest-value use case and what it takes to ship it.