Shakers for expert talent

Work as a Data Analyst

Projects where your analytical judgement decides: which KPI answers the business question and how it reads. Shakers connects you with companies that need to decide with data, aligned with your stack and availability.

The role reads in two places: a bootcamp syllabus and the job ad asking for "3+ years" of crossing spreadsheets. Neither tells you how to decide what gets measured per project, engagement by engagement. Here is that.

  • Higher-paying projects
  • More continuity between projects
  • Greater recognition for your experience
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Looking for data analysis 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 analyst decides every single week

A data analyst turns the data a company already measures into answers for deciding: cleaning and querying with SQL and Excel, crossing sources, building dashboards and communicating what the business should do with each figure. Unlike the data scientist, they train no models to predict: they explain what happened with data others prepare. And they consume the pipelines and warehouse the data engineer builds.

You decide which question each metric answers: the SQL query that calculates it, the cleaning that makes it reliable and the dashboard where it lives. You also decide what the report refuses to say: a KPI without a clear definition does not go in. The pipeline is not yours: you consume it, and you flag heavy transformation at kickoff.

SQLPower BITableauPythondashboardsKPIsdata cleaningA/B testingExceldata visualisationRBigQuery SQLData cleaningDashboardsKPI definitionPower BIA/B testing

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 analyst delivers on a Shakers project

At Shakers

The brief arrives with the decision

Shakers is hiring infrastructure: the project arrives with the question the company needs answered and its data, not a list of technologies.

Delivery

KPIs traced end to end

You deliver the dashboard and the why of each metric, including the one you dropped and the reason it stays out.

Operation

What happens when data changes

You set the refresh, what happens if a source fails and who answers for the number the day someone disputes it.

What we ask

Analysis used, not just delivered

Having measured real processes with SQL and Power BI and being able to tell which KPI failed, and what you did when data contradicted you.

Judgement

Power BI, Excel or Python

Choosing the tool for the question, not for fashion. Sometimes the honest answer is a spreadsheet, and saying so.

Boundary

How far your brief goes

You consume the pipeline; you don't build it. If the project needs moving data at scale, you say so at kickoff and don't absorb it.

Frequently asked questions

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

What is the difference between a data analyst and a data scientist?
The analyst explains what already happened with the data being measured; the scientist trains models that anticipate what comes. On the same base, the conversation you open differs.
Is it hard to become a data analyst?
The tool is learned quickly; judgement is not. What the certification measures is real deliveries: an analysis someone used to decide, not a course certificate.
Power BI or Excel as a data analyst?
Both. Excel is still the floor where you cross data; Power BI is the delivery layer with the strongest presence in live vacancies. The client's ecosystem decides.
How much does a freelance data analyst earn?
You invoice per project, and scope sets the band: number of sources, KPIs to maintain and data complexity. You agree the budget before accepting the engagement.
Can data analysis projects be done from anywhere?
Almost all: data lives in the cloud and sessions with the company happen remotely. Only the kickoff occasionally asks for in-person time.
How do I join Shakers as a Data Analyst?
Create your profile, pass the certification process and join the collective: only 4 percent make it. Then you choose which analysis projects to work on.
The day to day of the trade

The query crossing sales with operations, the KPI nobody knew how to calculate and the dashboard that gets abandoned if it answers nothing. Fewer school theories, more traceable decisions.

The BI layer is your tool identity

Power BI and Tableau lead delivery; SQL and Excel remain the floor: the delivery tool follows the client's ecosystem.

The barrier is judgement, not the tool

Tools are learned fast; judgement is not. Which metric goes in, which stays out and why: that is earned with real deliveries, and it is exactly what our certification measures.

How people arrive from other trades

The frequent door is advanced Excel turning into SQL, and SQL ending in dashboards. Another comes from finance: whoever crossed the numbers for a year knows the data better than anyone.

Roles that cross an analysis project

Four roles from the collective cross your path on an analysis project, from the one building the source to the one predicting with it.

Prediction

Data Scientist

Where your reporting ends up explaining what happened, theirs starts predicting what comes next on the same data.

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Piping

Data Engineer

Builds the pipelines and the warehouse you consume: when data doesn't arrive, your KPI stalls and so does the engagement.

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Reporting

BI Developer

When the report needs a model that holds on its own, the BI Developer designs the semantic one and you feed it.

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Sources

Backend Developer

Their APIs and databases are the origin of everything you measure: when the source is wrong, the dashboard lies.

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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 analysis decides?

Pass Shakers' certification and choose which analysis projects to join.