Fabian Werkmeister

I help you to become fluent in Data and enable you to translate between business & tech ★ Data Scientist @FUNKE ★ 🐍Python 🤖Data Science 🛠️Data Engineering

Why do so many data projects fail to deliver real business value?
Because they often start with a technical discussion, not a business problem.
➡️ And you've likely felt the same frustration as so many others...

Investing in a complex data solution only to find it's over-engineered, over-budget, and doesn't actually solve your core challenge.
You're left with high costs, slow processes and no actionable outcome.

Imagine instead a data solution that is simple, powerful, and cost-effective. One that feels like it was designed exactly for your business and just works.
This is what I can build for you.

I started my career on the business side and switched to data along the way, where my deep passion for that field motivated me to self-taught all the skills I now have.
Sitting on both sides of the table allowed me to really understand and connect both worlds.

This is what you get, if you work with me:

Business-First Approach:
You get a business-minded partner, which listens to your challenges first to ensure the solution we build together is one you actually need. No confusing tech-speak, just pure focus on actionable results for you and your business.

Pragmatic & Cost-Effective Solutions:
You get a lean, powerful, and low-maintenance data analytics platform on Google Cloud Platform, which simply works.

Collaborative & Transparent Process:
You will be a partner in the process, not a spectator. Through regular check-ins and feedback, we ensure alignment at every stage to build something, which actually helps you.

➡️ If you're ready to finally get results from your data, connect or DM me and let’s chat!

Data Scientist

No Budget for Managed ETL? 💰
Here is a lean and cost-effective alternative 👇 

Managed ETL services can kill your budget
They are designed to punish you for your growth
They feel essential, but their pricing will spiral as your data volume increases

But you can also build something yourself
Use dltHub and serverless functions / containers to perform data ingestion:
✅ You only pay for execution time, aligning cost directly with usage
✅ You can focus on the actual problem, since dlt does the heavy lifting for you

What's the biggest headache dlt solved for you recently? ✌ 

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Hi, I'm Fabian👋

I write about building lean and cost-effective analytics platforms on GCP

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Lean & cost-efficient data systems on GCP for businesses to finally turn their data into decisions | 🛠️ Senior Data Engineer @ FUNKE

I don't have a linear career in data.
For a long time, I let that be a limiting belief.

I studied economics and worked in that field for some years
I learned what KPIs are and what really drives numbers and businesses
I did a lot of powerpoints and fought with excel, but this wasn’t a profession for me

So I took a data science bootcamp and switched to data
I still remember how everyone in the bootcamp was way better at coding than me
For years in data, I felt I was always playing catch-up to the people who grew up with this stuff

But with time and more seniority, this perception shifted
I notice that using tech and tools doesn’t generate value on its own
Value is created in knowing when to use which tool to drive a business action

With this in mind, I began to see my non-linear career path as my biggest asset.
Since I lived in both worlds, I also know very well how to connect them.
I start with the action, then build the absolute minimal system for that.

I may not be the best coder or technical expert out there
But I speak and understand business language
And this enables true solutions

If you’re also coming from a non-traditional path, stop trying to fit the mold.
Your diverse background isn't a weakness.
It can be your ultimate advantage.


What’s an unexpected asset your career path has given you?

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Hi, I'm Fabian👋
I write about building lean and cost-effective data systems on GCP
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The biggest lie in data
"We just need a new tool"


A new tool won't fix a broken process.
A new tool won't magically create a data-driven culture.
The most successful projects follow a business-first mantra.
👉 Tools are the last piece of the puzzle.

✅ Focus on Culture: Talk with the business teams.
✅ Focus on Processes: How are things done right now and how should they work in the future?
✅ Focus on the User: Identify the friction points between the data and the action or decision taken by an end user.

Remember:
Tools are just the vehicle - culture and process are the engine!

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Hi, I'm Fabian 👋

I write about building lean and cost-effective data systems on GCP
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Stop obsessing over the architecture diagram.
Obsess over the problem.

❌ Typical data project goes like this:

Month 1-2: Vendor selection
Month 3-4: Pipelines and modeling
Month 5: Dashboarding
Month 6: Show it to the business
(and find out it’s useless)


✅ The Value Path looks like this:

1. The "Why" Phase (40% of effort)
Deep stakeholder interviews.
Find out problems and decisions to be made.
Don't write a single line of SQL until you know that.

2. The "How" Phase (10% of effort):
Lean tech selection.
Most tools deliver the same output.
Choose what is convenient and available.
(if possible choose also what is cheap)

3. The "Build" Phase (50% of effort):
Minimalist implementation.
Automating only what is necessary.
Build the shortest bridge between data & decision.


You can build a "perfect" scalable platform in 6 months that nobody uses

Or you can build an "imperfect" targeted solution in 6 weeks that changes the business.

—
Hi, I'm Fabian👋
I write about building lean and cost-effective data systems on GCP
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My data team was most often seen as a cost center.
Here is how we shifted this to become enablers 👇

I used to build the thing I was asked for.
I finished the tickets.
I delivered the code.

But that often left behind a black box solution that no one on the business side truly understood. 
A technical problem was solved without transferring the value of it to the business.
That's how data projects solely generate costs.

Do this instead
✅ Prioritizing the business problem over technical solutions.
✅ Designing the platform to deliver a single, clear business action.
✅ Measuring success by time or costs saved, not by processed data volume.
✅ Transferring knowledge so the business team can understand and act on the data without you.

That’s how you build trust.
That’s how you generate value tied to the costs.
That’s how your projects and your team are seen as an investment.

TL;DR
Any data project needs to directly and measurably impact the bottom-line of the business
➡️ if your project doesn’t deliver this, it will only be seen as a financial liability

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Hi, I'm Fabian 👋
I write about building lean and cost-effective data systems on GCP
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SQL is important for a data engineer
But the most valuable skill isn’t taught in tutorials

I’m not talking about Terraform, Python or BigQuery
These are merely tools and techniques to work with data
My most important skill is the ability to translate:

Business ➡️ Tech
Stakeholder: "I need real-time data for my weekly sales report"
Me: "We need a simple batch pipeline that updates data each morning"

Tech ➡️ Business
Tech: "We implemented incremental loading for big source tables"
Me: "Your Monday morning dashboard will now be ready at 8:00 AM instead of 10:30 AM."

When you bridge this gap with communication, you do two things:
👉 You protect the business from over-engineering (and over-spending)
👉 You work on things stakeholders actually care about (time and money)

Learn to speak and understand business language
That is how you move from a data engineer to a strategic business partner

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Hi, I'm Fabian👋

I write about building lean and cost-effective data systems on GCP
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The era of Big Data is over
The era of Big Action will finally unlock the value of data

For the past decade, billions were spent on data stacks
We now have 100+ tools to pipe, clean and visualize data
And yet, decision-making velocity hasn't improved

The systems we built were designed for observation, not operation
Your data system is worthless until that potential is converted into movement

Let's look at a simple example:
➡️ 100 customers haven't purchased in 3 months

𝐓𝐡𝐞 𝐨𝐥𝐝 𝐰𝐚𝐲
- Discover this (most businesses don't even get to this point)
- Download CSV
- Format in Excel
- Upload to HubSpot
- Manually trigger "we miss you" email
- By the time you do this, 50% of them have already moved to a competitor

❌ 𝗧𝗵𝗮𝘁 𝗶𝘀 𝗳𝗿𝗶𝗰𝘁𝗶𝗼𝗻 𝗮𝗻𝗱 𝘄𝗵𝗲𝗿𝗲 𝘃𝗮𝗹𝘂𝗲 𝗹𝗲𝗮𝗸𝘀 𝗼𝘂𝘁 𝗼𝗳 𝘁𝗵𝗲 𝘀𝘆𝘀𝘁𝗲𝗺


𝗧𝗵𝗲 𝗻𝗲𝘄 𝘄𝗮𝘆
- Your system detects these automatically
- Your system pushes these to HubSpot
- An email workflow is triggered
- You get a ping to approve this
- Emails are sent

✅ 𝗪𝗶𝘁𝗵 𝗺𝗶𝗻𝗶𝗺𝗮𝗹 𝗶𝗻𝘃𝗲𝘀𝘁, 𝘆𝗼𝘂 𝘁𝗼𝗼𝗸 𝗶𝗺𝗺𝗲𝗱𝗶𝗮𝘁𝗲 𝗮𝗰𝘁𝗶𝗼𝗻


Data systems need to pivot
From a reporting source to a trigger
From "what happened?" to action-oriented systems.


𝗪𝗵𝗮𝘁 𝘄𝗮𝘀 𝘁𝗵𝗲 𝗹𝗮𝘀𝘁 "𝗲𝘅𝗽𝗼𝗿𝘁-𝘁𝗼-𝗰𝘀𝘃" 𝗽𝗿𝗼𝗰𝗲𝘀𝘀 𝘆𝗼𝘂 𝗸𝗶𝗹𝗹𝗲𝗱? 😉 

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Hi, I'm Fabian Werkmeister👋
I write about building lean and cost-effective data systems on GCP
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I used to be a data snob
And this attitude prevented valuable solutions

As a data engineer, I think in terms of outputs
I designed whole workflows with a clear result in mind
This was most often a nice dashboard or an automated report

When someone asked for an "Export to Excel" button, I rolled my eyes
I thought "Why do I build of all this if it just ends in a spreadsheet?"
I was missing the point completely!

❌ My job isn't to dictate how people work.
✅ My job is to enable them to work.


If a finance manager is faster in Excel, my fancy dashboard is actually a bottleneck.
If a sales rep needs a CSV to close a deal, my shiny report is blocking revenue.
My business users know way better how they can work efficiently than I do!

👎 I stopped being religious about the tools
👍 I started being religious about the outcome


Now, my philosophy is simple:
👉 Build the pipeline
👉 Ensure the data is available and trusted
👉 Let the user decide the last mile to be actionable

If that means an Excel export or a csv-file?
So be it.

The result at the end of the day is what counts.
Not the tool they used to get there.

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Hi, I'm Fabian Werkmeister 👋

I write about building lean and cost-effective data systems on GCP

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Does your data project have a six-figure price tag?
Bad news, you’ve already failed

A six-figure data stack is not an investment.
It’s a financial liability.
Start with something super simple👇

✅ Identify the Core Problem:
Stop looking at tables and talk to people.
👉 What specific business problem is causing pain?
➡️ "We are spending $50k/month on ads, but I can't tell, which campaigns are actually driving sales"

✅ Define the Actionable Outcome:
Don't start to build before you have a clear goal in mind.
👉 What is the simplest, clearest decision or action that needs to be enabled?
➡️ "I need to see CPA by campaign side-by-side so I can cut the losers, if they fall under value X"

✅ Select the Minimalist Tool:
Only now, start to build something!
👉 What is simplest, most cost-effective setup to deliver that specific action?
➡️ Get campaign data via ETL-tool or scripts, build a simple SQL-pipeline with a cron job, pump it into something consumable for your end user (Excel, BI tool, etc.)

That's it.
That's how you build a fast MVP, which costs almost nothing.
And with this foundation you can iterate and scale up always later on.


What’s one business problem you solved recently where you intentionally chose a simple tool over a complex one? 👇 

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Hi, I'm Fabian👋
I write about building lean and cost-effective data systems on GCP
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Some people meditate.
I build pipelines.

There is a meditative quality to Data Engineering that I haven't found anywhere else.
It satisfies my deep need for organization.
Taking something messy and shaping it into a logical, reliable structure.

It’s like solving a massive puzzle.
Every piece has a place.
Every transformation has a reason (hopefully 😉).

Building pipelines also leads to another passion of mine: serving others.
I use my love for structure to make life easier for the people around me.
I take the complexity onto my plate so they don't have to deal with it.

It's the perfect synergy. 
Solving someone else's problem while satisfying my inner needs.
And that’s why I love what I’m doing each and every day! 


There's nothing quite like that feeling when your pipelines wrap up with a satisfying green checkmark, is there? 😉

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Hi, I'm Fabian👋
I write about building lean and cost-effective data systems on GCP
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Michel Brok 🎯

Tracking Architects

Tracking Architects empowers eCommerce and funnel website owners to maximize revenue from their marketing efforts through advanced server-side conversion tracking and data analytics.

Eigenaar

Team6

Team6 helps FMCG and retail businesses to improve business performance with data. Our focus is to make strategies work by bringing ways of working, data and technology together.

Founder

A.S. Watson Group

Helping the marketing team to use data to 1) make better decisions in target audiences, offerings and content and 2) increase relevancy and therefore increase customer lifetime value. 

Results:

- Created and implemented the CRM Data Strategy
- Implemented cross-functional CRM data team
- Implemented the CRM data-driven process
- Implemented algorithms for optimizing promos

Data Lead CRM a.i.

Danone

Leading 2nd Digital Transformation wave of the Dutch CBU for all Danone brands (dairy, plant based, medical & baby). Build the data foundation to take better decisions and actions to drive business value for the CBU.  

* Developed the data strategy and roadmap together with senior management
* Build the cross-functional data team overseeing data analytics, data science, architecture and platform
* Managed the local data platform and architecture (Azure) implementation
* Managed the integration of all digital channels in Azure data lake
* Delivered 3 use cases: customer 360 together with CDP, Marketing Mix Modeling & MROI (causal attribution)

Head of Data

Leading the Digital Transformation for the Benelux BU with focus on improved customer experience. 

* Building the digital environment and BU digital capabilities
* Transforming marketing strategy and operating model
* Shape and build the marketing technology stack, integrate within marketing operations
* Delivering and activation of digital products & services
* Leading design, experience, digital product & engineering teams

Head of Digital

E.ON

Responsible for e-commerce and digital marketing for the residential, SME market and large enterprises.

* Development and implementation of the digital transformation roadmap for the Benelux cluster
* Development and execution of the digital marketing & e-commerce strategy to drive brand awareness, customer acquisition, retention and NPS 
* Marketing technology: implementation of the Adobe CMS and migration existing digital platform, implementation of the customer self-service portal and connection between digital platform and SAP
* Management and optimization of traffic channels  SEA, SEO, affiliates, retargeting campaigns, display advertising and online partners
* Management and optimization of webconversion with A/B testing, data analytics and UX-optimization
* Implementation of the E.ON self service portal to increase self service and drive NPS and decrease costs
* Implemented Lean wow and performance driven mindset
* Managing and coaching multi-disciplinary online team (4 fte)
* Operational excellence day-2-day optimization working method

Team Manager Online Marketing

Essent

Responsible for online sales and lead generation for residential and SME market.

	Defined and implemented annual online sales plan, defined targets, budgets and weekly sales forecast
	Accelerated performance based sales & lead generation by optimize traffic sources (display advertising, SEA, SEO, affiliates) and CRO for Essent.nl. Managed referral and price comparison websites
	Implemented marketing campaigns ATL/BTL in online channels in collaboration with marketing and sales department 
	P&L responsible for digital sales

Digital Marketing Manager

Tribal

Helping clients driving business growth with developing and executing online marketing strategy focussed on increasing website traffic and conversion optimization.   

	Development and implementation of new online advertising campaigns to increase numbers of leads and / or sales
	Managed and optimized existing SEA and SEO campaigns
	Aligned projects with usability and web analytics experts 
	Evaluated campaigns by analysis with Google Analytics
	Reporting to customers and team lead

Online Marketing Consultant

Lensvelt Medical

Improving company awareness and developing customer service proposition to support customer acquisition and relationships.


	Development and implementation operational marketing plan
	Coordinated and implemented marketing activities such as product / price promotions, trade fairs, managed and implemented online advertising campaigns, website optimization and e-mail marketing
	development of services products and related concepts and responsible for activation via website, sales channel and fairs

Marketing Specialist

Marketing Automation & Data Expert | Helping retail & CPG to drive customer engagement at scale.

Business & Agency Owners – Listen Up:

The #1 reason your ad campaigns hit a wall?

INACCURATE DATA.

It’s the frustration holding back ambitious advertisers like you — those who are ready to scale but can’t break through.

At this stage, you’re trying to lower ad costs and increase value. But if the data you rely on is off, making the right decisions becomes nearly impossible.

Here’s the real issue:

Inaccurate data doesn’t just impact your decisions — it also sabotages the advertising algorithm.

The better your data, the better the algorithm can identify your best customers.

But getting accurate data and conversion tracking right is easier said than done.

That’s where the Data-Driven Scaling Formula comes in — putting accurate conversion tracking at the core of your strategy.

The Data-Driven Scaling Formula empowers ambitious business owners like you to scale faster by leveraging the right data at the right time.

The formula is made up of three key parts:

	1.	Enhanced Performance Tracking: Best-in-class server-side tracking combined with smart data usage throughout the entire customer journey. This ensures both you and the advertising algorithm are making better decisions and taking smarter actions.

	2.	Precision Algorithm Training: Fueling your advertising algorithm with high-quality data to significantly improve targeting. Now, you’re only spending money on customers who bring real value.

	3.	Transform Data into Growth: Gain control over your business’s growth by understanding what works — and what doesn’t — in both marketing and sales.

Curious about how we’ve helped others scale smarter?

Send me a DM, and let’s chat!

-----

Hi, I’m Michel – The Conversion Tracking Guy.

With over 18 years in Digital Marketing, I’ve witnessed firsthand how advertising platforms and marketing systems are becoming increasingly data-dependent. Yet, proper conversion tracking and data architecture are often overlooked because they seem complex or costly.

I’ve helped over 250 business owners unlock the full potential of their marketing with server-side tracking and analytics. In almost every case, the results were clear: a significant boost in performance.

Let’s talk about how accurate data can transform your business.

Co-Founder

AldrichX is a data-driven marketing agency that helps 6+ figure fashion eCommerce brands to grow their business whilst they can keep focussing on building their brands.

Ecom subscription sellers: 

Stop wasting your Meta Ads budget on returning customers.

Such an easy fix, yet almost nobody does it.

Every major Ecom platform already gives you the parameter you need, you just have to plug it into your tracking setup.

Once you tell Meta who’s new vs returning, everything changes:

- Cleaner attribution
- Less wasted spend
- Better audience signals

More budget going to actual new customers

Meta can’t optimize for what you don’t tell it, give it the right data, and it will find the right people.

Want help setting it up? 

You know where to find me ;)

Michel Brok

I train your ad algorithms to find your best buyers. Accurate conversion tracking + smarter buying signals = higher ROAS.

70% of your Google Ads leads are spam.
Real problem? You keep feeding Google… spam data.

So Google thinks those fake leads are exactly what you want, it finds you more of them.

Meanwhile, the good leads?
Google has no idea what they look like.

Here’s the fix:

- Mark qualified leads in your CRM
- Setup offline conversion tracking 
- Activate Enhanced Conversions
- Gather data in Google Ads 

Make the switch when everything looks good and feed Google with signals from high quality leads. 

Better signals = better leads

Still getting mad when I see this. 

You're spending 100k monthly on Ads and using a free tracking plugin 🤯 

Audited an e-commerce brand this week.
Meta was their ONLY growth channel.
Big budget. Big ambitions.

But they were only sending 60-70% of their data back to Meta.

Why?

The Facebook app in Shopify was not tracking all data. 

And then they wondered why:

> ROAS was unstable
> Scaling didn’t work
> Meta was “inconsistent”

The algorithm can’t optimize on blind spots (and it's getting worse).

So we fixed it:

+ Implemented a real data layer
+ Added server-side tracking
+ Passed email, phone, location
+ Captured click IDs

Result? 20-30% more conversions. Instantly.

DON’T save on tracking please 🙏

Meta and Google Ads numbers seem off… and you’ve already tried everything:

- Free plugins
- Agency experts
- YouTube tutorials
- Cheap freelancers
- In-house developers
- A fresh Google Tag Manager setup

But still, after 6 months you’re staring at numbers that make zero sense whilst your competitor absolutely crushing it.

Let's end this frustration once and for all.

Hire a tracking expert or agency, ask them:

1. How many times the've done the setup you need
2. How they measure accuracy and how to optimize for
3. If they have a 'second-pair-of-eyes' mechanism
4. What their monitoring process is

Time to stop doubting and start scaling with confidence.

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