Mateo
Full Stack Developer
ReactNode.jsPythonTypeScriptNext.jsMongoDBAWSAIAPIs
Shakers for companies
Work with a senior Data Engineer
A certified data engineer who builds what your reporting consumes: pipelines that reach production, ETL and ELT moving data from ERP or CRM, and a data warehouse every team queries with confidence.
Senior tech talent for your data architecture, starting in days on the stack you already have, without growing headcount.
- Certified talent in AI and agent skills
- Meet up to 3 AI Builders in 72 h
- Flexible collaboration models
+600
European clients across different industries
Top 4%
We work with the top 4% of certified talent in our community
72 hours
Meet 3 certified candidates in under 72 h
4.7/5
Our clients' satisfaction on Trustpilot
The talent mix your company needs
At Shakers you will find AI Engineers, Data Engineer and specialists across Tech, Product and Data
Ana
DevOps Engineer
DockerCI/CDAWSAzureKubernetesTerraformAmazon Bedrock
Lucas
Backend Developer
Node.jsPythonJavaGoPHPMySQLMongoDBDocker
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Emma
Security Engineer
Burp SuiteOWASP ZAPMetasploitNmapNessusTrivySnyk
Data Engineer: what this role brings to your project
A data engineer builds the infrastructure a company uses to move and prepare its data: designing ingestion pipelines, programming the ETL and ELT that transform it, organising it in a data warehouse and looking after orchestration and quality.
It is the role that makes everything else possible: the analyst consumes their pipelines to report, and the scientist trains models on the data they prepare. Daily work in SQL and Python, with Airflow to orchestrate and Spark or Kafka for volume.
SQLPythonETLELTdata warehouseAirflowSparkKafkaDatabricksSnowflakeKubernetesDockerAWSGCP
One provider. One contract. Full traceability
How Shakers works for your company
Post your project
Tell us about the project, its scope, the expertise you need and when you want to get to work.
You get three options
We match your brief against certified talent and introduce the three AI Builders who fit best.
The last word is yours
Meet the three specialists and choose who you collaborate with; we handle the rest.
Why work with Shakers
The advantages of adding this profile with Shakers
Pipelines that reach production
Ingestion from your ERP, CRM or APIs with documented transformations and scheduled refresh, not the script that dies every Monday.
ETL and ELT without redoing your architecture
Transformations over your source systems: data arrives clean at the warehouse without migrating what already works.
A warehouse every team queries
Data warehouse modelling with agreed schemas and definitions: the same figure for finance, sales and product.
Capacity without growing headcount
Data engineering by project, no hiring process: certified talent joining with your current access and systems.
Orchestration that depends on no one
Airflow or equivalents to schedule the refresh: the pipeline runs alone, warns when a source fails and keeps a log.
Data quality, not just movement
Duplicates, nulls and shifting schemas: every pipeline ships data with checks before anyone decides with it.
Frequently asked questions
Any other questions? Our team will answer them.
Tell us your data projectWhat is the difference between a data engineer and a data analyst?
The engineer builds the path of the data: pipelines, ETL and warehouse. The analyst consumes it to answer business questions. The classic mistake is buying dashboards with no infrastructure behind.
How much does a Data Engineer engagement cost?
Scope sets the price: number of sources, complexity of transformations and volume to move. The budget closes per project before starting, with no hourly surprises.
How long until the first pipeline is live?
With access to sources and one scoping session, the first ingestion with real data arrives in days. The full warehouse consolidates in phases.
External data engineer or in-house team?
The external fit is urgent data infrastructure or a bounded project; the in-house team, a continuous and growing flow. Many start external and decide later.
Can data engineering projects be done remotely?
Almost all of it: pipelines run in the cloud and sessions with the team happen remotely. Only the occasional on-prem deployment asks for presence.
What does a data engineer need to start?
Access to the data sources and one session to fix scope. With that, the first pipeline reaches production with no technical blockers.
What gets delivered in the first weeks
The first pipeline in production: ingestion from your sources, documented transformations and scheduled refresh. Every warehouse table has an owner and a cadence.
4,240 live UK vacancies mention data engineer
4,240 live UK tech vacancies mention data engineer, according to Shakers' market analysis (n=39,811, September 2026). Python leads the stack and the signals of the trade are Airflow, Spark and Snowflake.
Where the data engineer ends
They build the path of the data, not its interpretation: analysis belongs to the analyst and prediction to the scientist. If data isn't reaching production, this is the role.
Senior, because data doesn't forgive
A badly designed pipeline doesn't fail the day it's built: it fails the day someone decides with it. Scope is agreed before starting, and talent passes certification first.
Connect with AI specialists to build your next project
Find specialists in Tech, Product, Data to complement your team
Data Scientist
Trains models on the data your pipeline moves: without reliable data in production, prediction is worthless.
Data Analyst
Consumes your pipelines to build the KPIs and dashboards the business opens every single week of the year.
Backend Developer
Their APIs and databases are the origin of your ingestion: when clean data must come from development, they solve it.
AWS DevOps Engineer
The infrastructure your pipelines run on: automation, deployment and the cloud cost that carries the data.
The AI talent you need Certified by Shakers
We introduce you to three ready_to_build AI Builders in 72 hours.
