One data engineering outcome, scoped and shipped.

A 3 to 6 week engagement for a defined pipeline, dbt, warehouse or orchestration problem. We agree the acceptance criteria, implement the work, validate it and hand it over.

Typical duration
3–6 weeks
Engagement terms
From EUR 4,000

Is this the right fit?

A strong fit if

This engagement is a strong fit when…

The technical objective is already understood.

The internal team lacks capacity.

One outcome can be scoped and accepted.

The work needs focused execution.

Delivery must include validation and handoff.

Probably not a fit if

This engagement is not the right fit when…

×

The problem is still too unclear to scope.

×

Multiple unrelated workstreams must be delivered.

×

Priorities are expected to change daily.

×

The team needs indefinite ongoing support.

What you leave with.

At the end of the sprint, the agreed outcome is implemented, validated and handed over to your team.

One agreed engineering objective
Implemented scope
Validation against acceptance criteria
Tests where applicable
Documentation
Handoff and knowledge transfer
Remaining risks or follow-up work

Scope, price and boundaries.

From EUR 4,000 · 3–6 weeks

Final pricing depends on the technical objective, access requirements and agreed acceptance criteria.

Typically included

  • One defined engineering objective
  • Written acceptance criteria
  • Implementation
  • Testing and validation
  • Documentation
  • Handoff
  • Agreed communication cadence

What we need

  • A clear business or technical owner
  • Timely access
  • Acceptance criteria
  • Availability for decisions and validation
  • Access to relevant repositories and environments

Usually excluded

  • Open-ended backlog ownership
  • Continuously changing scope
  • Unrelated parallel initiatives
  • Ongoing production support after handoff
  • Major platform discovery outside the agreed scope

If the scope changes, the new work is recorded and reprioritized. Unclear engagements may need an Audit before a Sprint.

Acceptance criteria stay visible.

The objective, boundaries and success conditions are agreed before implementation. Validation results, documentation and remaining risks are included in the handoff so the outcome can be reviewed against the original scope.

How the engagement works.

Step 01

Scope and acceptance criteria

Define one objective, agree boundaries, and document success conditions.

Step 02

Implementation

Deliver the agreed technical scope in the relevant repository and environments.

Step 03

Validation

Test the result, review acceptance criteria, and resolve agreed defects.

Step 04

Handoff

Document the work, transfer knowledge, and identify follow-up actions.

Relevant technology for this engagement.

Data pipeline implementation · dbt development and refactoring · Data warehouse modelling · Airflow and Dagster orchestration · Testing and data quality · CI/CD for data workflows
Hands-on delivery in production stacks, not advisory-only.

dbt logo
Snowflake logo
BigQuery logo
Python logo

SQL

Airflow logo

Dagster

Answered before the first call.

Have a defined data engineering outcome to deliver?

Share the objective, constraints and target timeline. We will assess whether it fits a focused sprint.