This is a submission for the 2025 New Year Writing challenge: Compiling 2025.
Every data pipeline has its breaking point. Mine came in late 2024, throwing errors I couldn’t ignore. Logs showed signs of stagnation, over-processing, and the need for a refreshed perspective.
But here’s the thing: I don’t really have anything to complain about. I hold a classical Software Engineering degree in Artificial Intelligence. I’ve been in the tech industry since 2008, exploring languages, projects, and domains before landing in the data field in 2017. Today I have a fantastic role as a Senior Data Engineer at a company that builds a cloud data warehouse. What makes it even more meaningful is that I’m not just helping create the platform—I’m also one of its first users, relying on it daily in my work. On top of that I have my technical blog where I share my thoughts and learnings with a community of like-minded professionals.
By all accounts it’s a great setup. But when I think of myself, I can’t help but wonder: Am I Yet Another Data Engineer?
What makes me unique in a field filled with brilliant minds, cutting-edge tools, and constantly evolving technologies? What is it about data that still excites me? And then the harder questions: What if I’ve outgrown it? What if it’s time to explore something new?
These thoughts aren’t born out of dissatisfaction or burnout—they’re coming from a deeper desire to define who I am and what I stand for in this industry, though at times it feels like my 2024 pipeline was a Kafka topic stuck in an infinite re-consumption loop of self-doubt.
ImpostorSyndromeWarning: Credentials are valid, but confidence is underflowing
Being a data engineer is great, but sometimes it feels like just saying “I’m a data engineer” doesn’t tell the whole story. What else am I? What do I bring to the table that’s unique? These questions are part of the reason I often feel hesitant about self-presentation. Sure, I’ve been in the industry for years, but am I enough?
One way I’m addressing this in 2025 is by working toward the AWS Data Engineer certification.
I work with AWS daily and feel confident navigating its ecosystem to build data solutions. But "confidence" doesn’t always mean "complacency." There’s always more to learn, deeper systems to understand, and broader skills to master. That’s why I see certifications not just as badges to display on LinkedIn (though they’re nice to have), for me they serve two bigger purposes:
- Broadening Knowledge : Getting ready for a certification pushes me to explore beyond the usual tasks of my daily work. It gives me a chance to dive into tools, ideas, and situations I wouldn’t normally face, helping me grow as a professional.
- Creating Opportunities : Projects I take on while preparing for certifications can start small but they can grow into meaningful additions to my GitHub portfolio or even turn into pet projects that I can nurture over time.
ArchitectUpgradePending: Growing beyond data engineering
As a data engineer, I often feel like we’re the builders—the ones assembling pipelines, wrangling data, and making sure everything runs smoothly. Don’t get me wrong, it’s a challenging and rewarding role. But the sheer breadth of what falls under the “data engineer” umbrella—BI, engineering, DevOps—can sometimes feel overwhelming. It’s a field that requires you to wear many hats, and that can leave things feeling a little… dizzy.
Over time I realized that what truly excites me isn’t just building pipelines or solving day-to-day problems. It’s stepping back and asking the bigger questions: How will this system work? What metrics will define its success? How will it scale? What’s the financial impact? I enjoy looking at the entire system—how it lives, breathes, and evolves.
That’s when it hit me: what I love is data architecture. A data architect isn’t just someone who builds—they’re the ones who truly understand data at every stage of its journey. From the moment it’s created to when it’s archived, from its birth certificate to its retirement party, they see the big picture. They balance technical know-how with strategic thinking, and that’s exactly the direction I want to grow in.
For me working toward AWS certifications feels like a good place to start. You need to understand the platform you’re working with—know where you live, so to speak. But becoming a data architect isn’t something you can achieve with just a certificate. It’s about practical experience and that takes time.
I realize that part of growing into a data architect is learning from others—reading about their experiences, understanding what worked for them and what didn’t, and taking those lessons into my own work. It’s also about experimenting with my own projects, thinking critically about how they’re designed, and bringing all the elements together into a unified system. To keep myself on track I’m putting together a roadmap that includes diving deeper into system design, exploring real-world case studies and focusing on practical experience. I also understand that the AI hype isn’t going anywhere, and staying relevant means gaining some knowledge in this area too. That’s why I’m planning to take this course to build a solid foundation in AI. This journey isn’t limited to data engineering—it’s about broadening my perspective and building something meaningful. It’s a long path, for sure, but one I’m excited to explore.
DataSecurityAlert: Learning to protect what matters
Lately I’ve been thinking a lot about the responsibility that comes with handling data. It’s a mix of pride and fear—pride in building systems that work with massive amounts of information and fear of what could go wrong. With AI advancing so rapidly and data breaches making headlines every other week it’s hard not to feel the weight of it all.
The last thing I ever want is to be the cause of a data leak. It’s not just about the technical failure—it’s about the trust that would be broken, the harm that could be done. That’s why I’ve started diving into data governance. It’s not the flashiest topic, but it’s one of the most important.
For me data governance is about more than just policies or compliance. It’s about understanding how to handle data responsibly, from how it’s stored and accessed to how it’s secured and eventually deleted. This year I want to learn what it takes to ensure the systems I build are not just functional but also safe.
To get started, I’m working on a roadmap for myself. I want to understand the basics of governance frameworks, try out tools for managing metadata and cataloging data, and work on some practical projects to get better at securing pipelines. I also plan to explore related areas like data privacy laws and ethical AI.
I’ve already started exploring the topic with this book, but I’ll admit, it feels a bit heavy on filler content. If you’ve come across any books or blogs that offer real practical advice on data governance I’d love to hear about them.
FeedbackNotFoundError: Blogging output exceeds feedback input
I’ve always enjoyed writing—especially at work, where I’m the kind of person who loves creating detailed thorough documentation. I like making things clear and easy to understand for others and over time that love for writing spilled over into blogging. It felt like a natural way to share what I know and bring that same clarity to a broader audience.
Still, as much as I love it, I can’t help but wonder sometimes: Is anyone actually reading this? Does it resonate?
The struggle isn’t just about low engagement—it’s about the feedback loop. When you’re sharing your work with the world, especially technical content, it’s easy to get stuck in a vacuum. Without feedback it’s hard to tell what’s working, what’s helpful, and where to go next. Sometimes it feels like shouting into the void and waiting for the void to like, comment, and subscribe.
At the end of 2024 I decided to make a big change: I switched to a hosted blog so I wouldn’t be dependent on any single platform. I’ve already written about how I made the move here. So far I have two followers on my new blog—not exactly a crowd, but it’s a start. In 2025 I’m hoping to grow that audience and create a space where meaningful conversations happen.
This year I want to focus on improving that feedback loop. I know part of the process is experimenting with new topics or formats—like hands-on tutorials or storytelling-driven posts—but the harder part is finding the right audience. Honestly, it feels like I spend all my motivation and creative spark just writing the article, and then I’m supposed to have energy left to sell it?
But there’s no way around it. Promoting my blog means spending as much time sharing and engaging as I do writing. That means asking questions, encouraging comments, and joining conversations on platforms like LinkedIn or Reddit. It’s a tough balance, but I know it’s the only way to turn that void into a conversation.
AmbitionOverflowException: Too many parallel threads running in my career pipeline.
I have this habit of taking on way too much. Work projects, personal goals, side hustles—I want to do it all, all at once. The problem is, life doesn’t work that way. Threads start colliding, I get overwhelmed, and somewhere in the middle of it all my mental health starts taking a hit.
And then there’s the other side of me. When I work on something for too long, I just… stop. I lose the spark, and it feels impossible to keep going. I’ve learned that trying to tackle everything at once just doesn’t work for me. Instead, I need to treat my projects like processes—each one scheduled to run for a set amount of time before I switch to the next.
In 2025 I want to do things differently. I’ll set time aside for certifications, blogging, learning new skills, and everything else I want to pursue, but I’ll make sure they’re running one at a time. No more parallel threads competing for my attention—just a well-organized schedule that keeps me moving forward without burning out.
It’s not easy to admit that you can’t do it all at once, but it feels like the right call. If I can stick to my plan, 2025 might just be the year I finally find some balance.
Pipelines evolve and so do data engineers. As I look back on 2024, I see it as a year of figuring things out—debugging the parts of my life and career that needed a little extra attention. In 2025 I’m not just fixing those things, I’m working on building something better.
This year I want to focus on growing as a data architect, balancing my priorities, and finding ways to connect through my writing. It’s not about doing everything perfectly—it’s about making steady progress, learning as I go, and enjoying the process along the way.
Here’s to 2025—a year of growth, focus, and maybe a few exciting surprises.
Top comments (1)
looking forward to progress reviews!