Bench · Data engineers
Pipeline and warehouse engineers who care whether the number in the dashboard is correct, and can prove it.
$30 – $47 / hr · from $4,800 / month
If more than one is true, the problem is usually capacity rather than skill — and that is a different conversation.
Written as work, not as keywords. If your problem is not on this list, say so on the call — we will tell you honestly whether it is ours.
Orchestrated batch pipelines in Airflow, Dagster or Prefect, with idempotent tasks, backfills that do not corrupt history, and alerts that fire on the right thing.
Dimensional models in dbt, tested and documented, so that 'revenue' has one definition and a lineage graph to back it.
Kafka, Kinesis and Flink for the cases that genuinely need sub-minute data — and a clear argument when batch is the better answer.
Contracts, freshness and volume tests, anomaly detection, and a quality report the business can read without a translator.
Query and storage profiling, clustering, materialisation strategy and warehouse sizing. Usually the fastest ROI on this list.
Semantic layers, metric definitions and reverse ETL, so the work reaches the tools your team already opens each morning.
We work inside what you already have. Nothing on this list is a recommendation to migrate.
Orchestration
Warehouses
Processing
Ingestion & quality
Full-time, one engineer, includes data model review.
| Role | Seniority | Rate |
|---|---|---|
| Data Engineer | Mid-senior · 3–5 yrs | $30 – $38 / hr |
| Senior Data Engineer | Senior · 5–8 yrs | $38 – $47 / hr |
| Analytics Engineer | Senior · 4+ yrs | $31 – $40 / hr |
| Data Platform Lead | Lead · 8+ yrs | $50 – $64 / hr |
Rates are per hour for full-time engagement and include our management, review and replacement guarantee. Part-time and pod pricing differ — see services.
Working to a fixed budget, or need part-time, long-term or several engineers? Those price below the card.
Contact for pricingEvery role, every rate, our standard MSA and NDA, and the two-week trial terms. No call required to read it.
No two-week onboarding. The first week produces something you can read.
Daily reporting run after an Airflow and dbt rebuild
Reduction in a client's monthly warehouse spend
Agreed definition of revenue, which is the whole point
The same five steps regardless of discipline.
You describe the gap. We tell you which discipline it actually is — that answer changes about a third of the time — and whether we have the person.
Real engineers with availability, not a database dump. Each one comes with a written note on why they fit and where they would struggle.
Your process, your bar, your rejection. We do not present anyone we would not hire ourselves, and the engineer who interviews is the engineer who ships.
They join your standups and open real pull requests. Stop inside the trial for any reason and the engagement ends there.
Monthly rolling from there. A senior lead reviews their work independently of you, and we tell you before you have to ask.
AI compliance platform
A self-hosted platform that audits contracts against GDPR, HIPAA and SOC 2 and returns cited, severity-ranked risk reports — with inference running on the customer's own GPUs, so no document leaves their network.
Yours. We have engineers deep in Snowflake, BigQuery, Redshift and Databricks. We are not a reseller for any of them and get nothing from a migration.
You do, throughout. Everything lives in your repository and your warehouse from day one. There is no Avexo platform to be locked into.
Often, yes — most of our data engineers are comfortable in dbt and BI tooling. For heavy stakeholder-facing analytics we would suggest pairing with an analytics engineer.
Most teams start with one engineer and add a second from a neighbouring bench within two quarters.
Engineers who have taken an LLM feature past the demo — through evaluation, latency, cost and the failure modes that only appear with real users.
Service and API engineers who have carried a pager, and who write the boring, well-tested code that keeps you off one.
Infrastructure engineers who reduce the number of things that can page you, and who treat your cloud bill as an engineering artefact.
Thirty minutes, an engineer on the call, and two or three real profiles within five working days.