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.”
Join ShakersShakers for expert talent
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.




















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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.”
Join Shakers
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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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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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.”
Join ShakersA 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.
Free to join, no hidden fees
Tell us who you are, what you can do, the projects you want to work on and what your availability and rate are.
We certify your experience and your use of AI so companies understand and trust what you bring.
We connect you with well-paid projects that fit your expertise and your preferences.
Work on real projects, with teams that need your expertise, without wasting time looking for opportunities.
Work with companies that need your stack and experience to take their projects to production.
Our AI matching connects your profile with the projects that fit your preferences.
Set your own terms based on your seniority. We manage contracts, payments and paperwork.
Shakers is hiring infrastructure: the project arrives with the data sources and their cadence, not a list of technologies.
You deliver the ingestion, the documented transformations and the log of every run, including the table you dropped and why.
You set the refresh, what happens when a schema shifts and who answers for the number the day a source fails.
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.
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.
You build the path of data; interpretation and dashboards belong to others. If the project asks for analysis, you say so at kickoff.
Any other questions? Write to us and we will reply.
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.
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.
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.
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.
Four roles from the collective cross your path on a data project, from the one interpreting results to the one holding the infrastructure.
Consumes your pipelines to build the business KPIs: when data fails, the dashboard lies and the engagement stalls.
Trains models on the data you prepare: without reliable data in production, prediction is worthless.
Their APIs and databases are the origin of your ingestion: when the source is wrong, your pipeline warns and their brief starts.
The cluster and the cloud cost your pipelines run on: without automation, data refreshes whenever it remembers.
The boundaries between these roles are agreed on each project: the title does not set them.
Take the next step with Shakers
Pass Shakers' certification and choose which data engineering projects to join.