Data Platform Build
Every team reads the same numbers
We design and build your data platform: ingestion, warehouse, modelling, BI and AI. Then we hand it over to a team trained to run it. We aim to have the first dashboard leadership trusts live within the first two sprints.
Book a free discovery call Teams we have built data for
Snap FinanceEmbrokerCigna HKENT Credit UnionEnclave
The problem
01
The in-house build has stalled
Your first data hire spends the week fixing pipelines. Each new source adds another script that breaks.
02
Nobody has built one before
Your team is capable, but designing a warehouse, semantic layer and orchestration from scratch is new to them. Mistakes here lead to a rebuild.
03
You pay for tools you can’t use well
Snowflake, Looker and dbt are in place, yet leadership meetings still start with arguments about which number is right.
One platform for your team and your AI tools
Designed properly from the start
Most platforms fail at the foundation. We model how your business works once, in code, and define every metric in one place. Your BI tools and AI agents then read the same definitions.
What you get
- Automated pipelines from each core source
- A tested, documented dbt model of your business
- One set of metric definitions
- Dashboards leadership uses every week
- A team trained to extend the platform
What we deliver
What the engagement includes
Each engagement has a fixed list of deliverables, agreed before work starts.
Automated pipelines
Managed ingestion from your product, CRM, finance and marketing tools, with orchestration, alerts and freshness checks.
Architecture and modelling
A layered warehouse design and a dbt project with tests, docs and CI. Business logic lives in version control.
Semantic layer
Metrics defined once in a semantic layer such as Cube or LookML, then served to your BI tools, apps and AI agents.
Dashboards and AI
Your first executive, finance and product dashboards, plus plain-English questions answered from the same numbers.
Enablement
Pairing, code review and runbooks, so your team can own the platform after handover.
Our method
How the work runs
01
Goals
Agree which decisions the data needs to support over the next 12 months.
02
Requirements
List sources, stakeholders, questions and data quality gaps.
03
Architecture
Choose a stack that fits your scale, skills and budget.
04
Roadmap
Plan sprints so each one delivers something usable.
Tools we work with
BigQuerySnowflakedbtDagsterFivetranAirbyteCubeLookerEmbeddable
Is this for you?
This works best if
- You have recently hired your first data person, or plan to
- Most reporting happens in spreadsheets and CSV exports
- You want to own the platform yourselves
How soon will we see something working?
The blueprint takes two to four weeks. The first production dashboard usually ships within the first two build sprints.
Do we need a data team already?
No. We can build the platform and help you hire. If you already have a team, we work alongside them so the knowledge stays with you.
Which warehouse should we use?
Usually BigQuery or Snowflake. The blueprint recommends one based on your cloud provider, data volumes and team skills, and explains why.
How we work
How an engagement starts
The work runs in three steps. You see working output within weeks and can stop after any stage.
01
Discovery call
A 30 minute call with the engineer who would do the work. We look at your setup, tell you what we would fix first, and whether you need us for it.
Day 1 02
Blueprint sprint
We map your sources, stakeholders and goals, then give you an architecture and a prioritised roadmap. You keep it whether or not we do the build.
2 to 4 weeks 03
Build in sprints
We ship working tracking, models, dashboards and agents every two weeks. You can stop after any sprint, and everything built stays yours.
Every 2 weeksWhat happens on the call
Book your call- 30 minutes with the engineer who would do the work
- No slides or sales pitch
- A clear answer on whether we can help, and a referral if we can’t
- The first fix we would make, which you can use either way
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