Frame the decision
Agree the question the work must answer, who owns the answer and what would change if the answer were different.
Written decision brief and success criteria
Data Engineering
Pipelines & Data Platforms
Ingestion, transformation and storage that holds up under change.
Problems we are called for
- Pipelines that fail silently
- No idempotency or replay
- Schema changes breaking downstream consumers
Scope of work
- Ingestion design
- Transformation layer
- Orchestration
- Data quality checks
How the engagement runs
- Assessment
- Design
- Build
- Operation
What you receive
- Pipeline implementation
- Quality checks
- Operating documentation
Related
Other work in this practice
Operating position
How we think about pipelines & data platforms
Most Pipelines & Data Platforms work fails long before delivery: the problem is described as a tool choice rather than a system constraint. We start from the decision the organisation must be able to make, then work backwards through the data, interfaces and failure modes that decision depends on.
Work in Pipelines & Data Platforms is usually inherited rather than designed. Systems accumulate interfaces, exceptions and undocumented behaviour until change becomes expensive. Our first contribution is an honest map of what exists, what it costs and what can safely be removed.
Engagement stance
We would rather narrow a scope than broaden a promise. Engagements are quoted individually after scoping, and we state clearly where the work stops.
Signals
When clients bring us in
A decision is blocked because nobody can state how the current system actually behaves.
Delivery slows every quarter while the codebase and integration surface grow.
Risk, security or compliance reviews keep arriving after design is fixed.
Results are demonstrated in controlled conditions but not reproducible in operation.
If none of these describe pipelines & data platforms in your organisation, a short scoping call is usually a better use of time than a proposal.
Landscape
What we look at first in pipelines & data platforms
Before any recommendation, we build a shared picture of the ground. These are the six things we examine, in this order.
01
Constraint map
The physical, regulatory and contractual limits that a plan cannot design around, stated before options are drawn.
02
Data lineage
Where the numbers come from, how they are transformed and which of them can survive an external challenge.
03
Change path
How a change reaches production today, how long it takes and where it waits.
04
Ownership
Named responsibility for each critical component, including the parts currently owned by nobody.
05
Evidence path
What is measured, what is only asserted, and what would have to be measured to settle the open questions.
06
Exit conditions
What must be true for the engagement to end well, written at the start rather than negotiated at the end.
Method
How the engagement runs
A typical pipelines & data platforms engagement moves through five stages. Each stage ends with something you can read, test or hand to someone else.
Establish the current state
Read the system as it is — code, data, interfaces, operations and the informal knowledge holding it together.
Current-state map with confidence levels
Test the constraint
Probe the assumption most likely to break the plan: throughput, latency, data quality, cost, regulation or ownership.
Measured findings and reproducible method
Design the option set
Present two or three defensible options with consequences, cost drivers and what each forecloses.
Option comparison and recommendation
Hand over deliberately
Transfer the material, the reasoning and the operating responsibility so the work continues without us.
Handover pack and named owners
Questions
The questions this work answers
Most pipelines & data platforms engagements start because one of these has no confident answer.
01
Where is the single point of knowledge that is not written down?
02
What does this vendor claim, and how would we test it against our own data?
03
Which constraint sets the schedule — and is it real or inherited?
04
What does good look like, expressed as a number rather than an adjective?
05
Who owns this on the day we leave?
06
What is the cheapest experiment that could prove us wrong?
Capability
Where we can take pipelines & data platforms
Engagements usually begin at one of these layers and move outward only when there is a reason to.
- 01
Diligence
A short, sharp read of technology, team and risk against the decision actually in front of you.
- 02
Design
Option sets with consequences, not a single recommendation presented as inevitable.
- 03
Engineering
Working software and infrastructure in your environment, under your review, with your tests.
- 04
Transfer
Documentation written for whoever inherits it, and a handover that is attended rather than emailed.
Outputs
What you receive
- A written findings document with method and confidence stated
- A current-state map of systems, data and interfaces
- A prioritised option set with cost and risk consequences
- A decision record the board or sponsor can act on
Engagement boundary
What pipelines & data platforms work covers
- Bounded builds with explicit interfaces
- Embedded delivery capacity alongside your team
- Documentation written for the people who inherit it
What it does not cover
- — Open-ended staffing without a defined objective
- — Work we cannot evidence or hand over
- — Reselling or recommending tools we have not tested
Formats
Ways to work with us
Any of these can carry pipelines & data platforms work. Pricing is quoted after scoping; there are no published rates.
45 minutes, no charge
Scoping call
We establish the decision you need to make and whether BELTO is the right party for it. If we are not, we say so and point you somewhere useful.
A written summary of what we heard
Two to four weeks
Assessment
A bounded, independent read of the current system with a stated method, ending in findings your team can challenge line by line.
Findings document and option set
Scoped per project
Delivery engagement
Design and build against agreed acceptance criteria, in increments, with evidence attached to each one.
Working system plus handover pack
Fixed term, renewable
Embedded capacity
Senior engineering alongside your team under your direction, with an explicit objective and an agreed end date.
Delivered work and documented practice
Reading
Related thinking and published work
Published positions, research and technical case studies that inform our pipelines & data platforms work.
Questions
Practical questions
- How quickly can pipelines & data platforms work start?
- Scoping calls are usually available within a week. Assessment work typically starts two to three weeks after a scope is agreed, depending on access and availability.
- What do you need from us to begin?
- A named owner for the decision, access to the systems and people involved, and agreement on what the engagement must produce. Everything else we can build from there.
- Do you publish rates?
- No. Work is quoted individually after scoping, because the same title can describe a two-week read or a six-month build.
- Can you work alongside our existing suppliers?
- Yes. We define interfaces and responsibilities in writing so accountability stays clear, and we do not take engagements that depend on displacing a supplier to succeed.
- What happens at the end?
- We hand over in an attended session, leave runbooks and ownership in place, and end at a written decision rather than an open retainer.
Next step
Discuss pipelines & data platforms
Engagements are scoped and quoted individually; there are no published rates. A first call establishes the decision you need to make, the constraint that governs it and whether BELTO is the right party for the work.
One-pager
Take this away as a PDF
Pipelines & Data Platforms — BELTO one-pager
A single printable page covering what we do here, how engagements run and what to send us to start. Useful for forwarding internally.
PDF · 388 KB