Shakers for expert talent

Work as a Data Engineer

Projects where the data is yours: what gets ingested, how it transforms and with what cadence it reaches the warehouse. Shakers connects you with projects aligned with your stack, rate and availability.

The role reads in two places: the job ad asking for "3+ years" across ten technologies and the school guide explaining what a pipeline is without ever living one. Neither tells you how to build a company's data infrastructure project by project. Here is that.

  • Higher-paying projects
  • More continuity between projects
  • Greater recognition for your experience
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Looking for data engineering projects
Allianz
BBVA
Bankinter
Microsoft
Qida
Accenture
Deloitte
Dcycle
HP
Línea Directa
Podo
Clicars
Sonosuite
Eroski
Civitatis
Alten
Vivla
Wayra
Cabify
Affinity
+3,000

Tech projects published on Shakers

+90

Tech, Product and Data specialisms are part of Shakers

6 months

Average length of a project with Shakers

4.7/5

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Portrait of Álvaro, Data Scientist in the Shakers collective Ready to build

Álvaro

Data Scientist

“In a climate this uncertain, Shakers gives you a layer of reassurance and confidence. What I like most, without a doubt, is the flexibility and getting to work on top-tier projects.”

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Amelia

AI Agent Developer

“I have been building AI agents for years. Thanks to Shakers I stopped chasing clients and started genuinely choosing which projects I wanted to work on. I work with some of the best companies in Europe, at my own rate, and I focus on what I am good at and what I love: building.”

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Portrait of Luz, Backend Developer and Data Engineer in the Shakers collective Ready to build

Luz

Backend Developer & Data Engineer

“Shakers adds a lot of value because it connects you with sharper projects, already filtered and better defined. It saves you a big part of the upfront work of understanding the client, quoting and weighing up whether it is worth it, and that means that as a contractor you can go far more directly to the opportunities that genuinely fit you.”

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Rubén

Software Developer

“Life as a contractor has a lot going on and it is not always easy. We like to focus on what we are good at, but you also have to manage clients, invoicing and go looking for work. For me, Shakers has been key because it does that prospecting for me, it gives the client confidence from the very first moment, and it lets us be part of a community with real enthusiasm.”

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Alejandro

AI Developer

“Shakers was key to getting my company off the ground: it gave me the flexibility to keep contracting while I built my next chapter. Without Shakers, I would have had to raise funding or push the project back.”

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Portrait of Toño, Product Designer in the Shakers collective Ready to build

Toño

Product Designer

“With Shakers I have landed recurring projects that give me peace of mind and room to grow professionally. It is not just about reaching quality clients: it is feeling that you have a network behind you, one that connects you with real opportunities and helps you move forward as a freelancer.”

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What a data engineer decides on every project

A data engineer builds the infrastructure a company uses to move and prepare its data: ingestion pipelines, ETL and ELT transforming it, data warehouse with orchestration and quality under control. Unlike the analyst, they don't interpret the data: they make it arrive. Unlike the data scientist, they don't predict: they build what the models need. The trade runs on SQL and Python, with Airflow to orchestrate, Spark or Kafka for volume and Docker and Kubernetes to deploy.

You decide how data enters: ingestion from ERP or CRM, the ETL or ELT that transforms it, the orchestration scheduling the refresh and the quality checks that let only reliable data through. You also decide the warehouse schema and which table doesn't ship: a pipeline without an owner doesn't go in.

SQLPythonETLELTdata warehouseAirflowSparkKafkaDatabricksSnowflakeKubernetesDockerAWSGCP PipelinesETLData warehouseOrchestrationData qualityIngestion

Free to join, no hidden fees

How Shakers works for talent

Join Shakers

Create your profile

Tell us who you are, what you can do, the projects you want to work on and what your availability and rate are.

Get your certification

We certify your experience and your use of AI so companies understand and trust what you bring.

Match with projects

We connect you with well-paid projects that fit your expertise and your preferences.

Specialist sitting on a sofa with a tablet and a Ready_to_build label

Data and Analytics projects that live up to your expectations

Work on real projects, with teams that need your expertise, without wasting time looking for opportunities.

  • Projects that fit you

    Work with companies that need your stack and experience to take their projects to production.

  • Opportunities that come to you

    Our AI matching connects your profile with the projects that fit your preferences.

  • You build. Shakers handles the rest

    Set your own terms based on your seniority. We manage contracts, payments and paperwork.

What a data engineer delivers on a Shakers project

At Shakers

The brief arrives with the source

Shakers is hiring infrastructure: the project arrives with the data sources and their cadence, not a list of technologies.

Delivery

A pipeline that holds on its own

You deliver the ingestion, the documented transformations and the log of every run, including the table you dropped and why.

Operation

What happens when data changes

You set the refresh, what happens when a schema shifts and who answers for the number the day a source fails.

What we ask

Pipelines in production, not mock-ups

Having moved real data with SQL and Python and being able to tell which pipeline fell over, and what you did when the schema changed unannounced.

Judgement

ETL, ELT or neither

Choosing the pattern for the volume and latency of the problem, not fashion. Sometimes the honest answer is a view over the source, and saying so.

Boundary

How far your brief goes

You build the path of data; interpretation and dashboards belong to others. If the project asks for analysis, you say so at kickoff.

Frequently asked questions

Any other questions? Write to us and we will reply.

What 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. On the same infrastructure, the conversation you open is different.
What is worth studying to work as a data engineer?
SQL is the language, Python the engine. A vendor certification or a bootcamp opens the door, but what gets measured are deliveries: a pipeline in production beats any syllabus.
Which tools are used daily?
SQL and Python daily, Airflow to orchestrate and Spark or Kafka when volume grows. The exact platform follows the client's ecosystem, not fashion.
How much does a freelance data engineer earn?
You invoice per project, and scope sets the band: number of sources, volume to move and complexity of transformations. You agree the budget before accepting.
Can data engineering projects be done remotely?
Almost all of it: pipelines run in the cloud and sessions with the company happen remotely. Only the occasional internal deployment asks for presence.
How do I join Shakers as a Data Engineer?
Create your profile, pass the certification process and join the collective: only 4 percent make it. Then you choose which data projects to work on.
The day to day of the trade

The ingestion that breaks when the schema changes, the transformation nobody documented and the pipeline that runs every morning without watching anyone. Less school theory, more pipelines in production.

The market asks for senior

4,240 live UK tech vacancies mention data engineer, according to Shakers' market analysis (n=39,811, September 2026), and seniority dominates: whoever decides with data cannot afford a failing pipeline.

How people arrive at the trade

Several doors: a vendor certification, a bootcamp or your own projects. The one that counts at Shakers is delivery: every pipeline leaves ratings that open bigger projects.

What this role is not

Not a backend engineer who stores data, not an analyst writing SQL. If your strength is querying and dashboards, your role is data analyst; if it's the predictive model, data scientist.

Roles that cross a data project

Four roles from the collective cross your path on a data project, from the one interpreting results to the one holding the infrastructure.

Interpretation

Data Analyst

Consumes your pipelines to build the business KPIs: when data fails, the dashboard lies and the engagement stalls.

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Prediction

Data Scientist

Trains models on the data you prepare: without reliable data in production, prediction is worthless.

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Sources

Backend Developer

Their APIs and databases are the origin of your ingestion: when the source is wrong, your pipeline warns and their brief starts.

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Infra

AWS DevOps Engineer

The cluster and the cloud cost your pipelines run on: without automation, data refreshes whenever it remembers.

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The boundaries between these roles are agreed on each project: the title does not set them.

Take the next step with Shakers

Want projects where data arrives reliable?

Pass Shakers' certification and choose which data engineering projects to join.