Data Engineering, delivered
by vetted seniors
24h
first response
72h
from brief to shortlist
1 in 7
clears our vetting
75/100
the pass mark
Mahala places senior Data Engineers into enterprise and government teams building production pipelines, real-time systems, and platform reliability in regulated environments. Every profile scored against our vetting protocol before it reaches your shortlist.
What a wrong data engineering hire costs
A wrong hire in data engineering is where hiring mistakes surface last and cost most. A failure cascades into every dashboard, model, and decision downstream. By the time it is clear, it has become an incident.
That is why we score Data Engineers on delivery evidence. Anyone can name Kafka. The question is whether they have operated it, at volume, under SLA, with the know-how to know what broke before the business does.
What our Data Engineers deliver
01
Production pipelines, real-time streaming, and warehouse or lakehouse architecture: Snowflake, Databricks, Kafka, dbt, Airflow, Spark.
02
Data platform reliability for high-volume regulated environments: observability, data quality gates, cost control, governance.
03
Migration of legacy ETL and orchestration stacks to modern, observable platforms without breaking what the business runs on.
04
The infrastructure work that doesn't tolerate junior mistakes.
When teams
choose Mahala
The engineers on our bench deliver when it is most needed: they have built and operated production systems for European banks, insurers, and energy operators, and they work inside regulated remote environments: your VDI, your perimeter, your security policies, from week one.
We do not run open marketplaces. Every Data Engineer on the bench has cleared our vetting protocol: scored on evidence across technical depth, demonstrated impact, consulting aptitude, and career trajectory. 75/100 is the gate. Six out of seven don't make it.
How an
engagement runs
- Brief us: role, stack, project phase, timeline, access model (VDI).
- We talk it through: a short call to sharpen the brief.
- Two or three blind CVs within 72 hours of a clear brief.
- Interview the finalists, choose the best fit.
- Mahala handles contracting, screening where required, and onboarding. One contract, one monthly invoice.
Representative
profile
Senior Data Engineer, eight years across French enterprise clients: national rail, tier-one banking, energy. Built and runs the real-time punctuality data warehouse (Azure, Databricks, Spark, Airflow) that supported Olympic Games operational coordination and secured a performance bonus tied to contractual punctuality commitments. At a tier-one bank, built the regulatory credit-risk engine that cut a multi-day manual process to under one hour. Vetted at 85/100.
Related
questions
What does a senior Data Engineer at Mahala typically work on?
Production pipelines, real-time streaming, lakehouse and warehouse architecture, ETL modernisation, and the platform-reliability work that high-volume regulated environments depend on.
How do you vet Data Engineers?
Two layers of institutional-grade assessment. Layer one verifies technical depth and documented delivery evidence. Layer two assesses consulting capability and compliance readiness. Full process →
Do your engineers work in VDI or Citrix environments?
Yes. Most of our enterprise placements operate in VDI or Citrix. We confirm access requirements in the brief and only send specialists with the operational discipline for regulated remote work.
What's the typical engagement length for a Data Engineering role?
Most engagements run 3 to 12 months, with extended retainers for multi-year platform programmes. We do not lock you in beyond what makes sense for the work.
How fast can a Data Engineer start in our environment?
Shortlist in 72 hours. Contracting and onboarding through Mahala.ai B.V. typically takes a further five working days. Most placements are working in your environment within two weeks of brief.