Pipeline reliability
Review agreed load failures, refresh delays and recurring recovery work. Prioritise fixes within the reserved capacity and response windows.
BIGQUERY / GOOGLE CLOUD
Keep it reliable. Keep moving forward.
Reserved specialist capacity for your BigQuery warehouse and Composer/Airflow pipelines. Planned maintenance, measurable improvements and a prioritised backlog.
Describe your project
Scope, availability and price agreed before work begins.
Query and cost efficiency
Review workload patterns, reprocessing and costly SQL. Measure the effect of agreed changes against a documented baseline.
A prioritised improvement backlog
Adapt models, connect sources or evolve selected architecture components. Plan small changes; larger projects receive their own scope.
Operation your team can own
Maintain agreed checks, run instructions and a change log. Review outcomes and next priorities together each month.
WHAT A MONTH COULD LOOK LIKE
Ongoing work you can follow.
An illustrative cycle, adapted to the agreed workflows and capacity. Maintenance and improvements share one visible backlog.
Review
State of covered workflows, relevant failures, freshness and consumption.
Prioritise
Choose the fixes and improvements that fit the reserved capacity together.
Improve
Make approved changes with tests and a decision log.
Close the month
Share completed work, capacity used, risks and the next priority.
View a sample monthly update
FICTIONAL DATA / NOT A CLIENT CASE
- Covered assets
- One DAG and its destination table; the rest of the platform is outside this example.
- Illustrative capacity
- 8 hours reserved · 6.5 recorded · 1.5 available this period. This is not an offer of availability.
- Work and check
- Adjusted DAG recovery; tested replay without duplicates and updated the run instructions.
- Open item and risk
- Confirm deletion handling with the source owner; leave that logic unchanged until clarified.
- Next decision
- Prioritise a late-data check within the remaining capacity. Extra hours and carryover follow the agreement.
If an issue comes up
Report it through the agreed support channel with the affected workflow and impact. It is reviewed within the contracted window and prioritised with you; work beyond coverage or capacity needs a separate decision. An urgent issue outside coverage follows your team’s internal escalation.
Assets, capacity, windows, channel, owners and time-consumption rules are confirmed before contracting. Planned service, without 24/7 on-call coverage or unlimited resolution.
HOW IT WORKS
A clear first step. Room to build trust.
Start by email. Agree the work. Keep decisions and documentation in your hands.
- 01
Describe the problem
Share the context in writing. The initial fit check by email is free; a technical conversation can be arranged when useful.
- 02
Agree a first engagement
Get scope, deliverables, access, dates, acceptance criteria and the total price. Accept the proposal and pay online through a private link.
- 03
Check the improvement
Receive documentation of the work and how to validate it. Continue with planned support if useful. Production changes require authorisation, tests and rollback.
LET’S START WITH THE CONTEXT
What would you like your data platform to do better?
Tell me what is happening and the outcome you need. My first reply will confirm the fit and a next step, or ask for the details needed to define it.
- No mandatory sales call
- No credentials needed to inquire
- No payment before an agreed scope