Data Analyst → Data Engineer, in public 🔧 Building data pipelines, cloud infrastructure & learning AI systems. AWS Certified | Python | Data Lead @Tiqra
Ilorin, Nigeria
Joined December 2023
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30 days ago I thought data engineering was “learn AWS + write SQL.”
Then I spent an afternoon staring at connect ETIMEDOUT :5432 while everything on paper looked fine.
Security group ✅
Port 5432 ✅
My IP allowlisted ✅
Still dead.
Wrong endpoint. Instance not public. Network first, app later.
That’s the job.
A store like Jumia can’t freeze checkout because payment, warehouse, inventory, and email all want to finish at the same time. So the order hits a queue and the rest of the system catches up. SQS stopped being a buzzword the day I pictured Black Friday.
Same with SQL. “Show me sales” is not a question. “Products that sold last week, no refunds, by channel” is. I learned that the hard way on joins — first LeetCode join cooked me, the next ones were easy once I asked what row I was trying to keep.
Day 1–30/100. Not an expert. Clearer than Day 1.
What I actually did: → AWS: Well-Architected, IAM, S3 site I hosted myself, VPC/TGW, Cognito, CloudFormation, CDNs, SQS/SNS → Debugged a real RDS timeout instead of only watching labs → SQL with Baraa + LeetCode (joins, windows) → SaaS cohort retention + MRR churn in MySQL + Tableau
Lessons I’m keeping:
Tool = problem it solves, not a vocab list
Debug in layers. Guessing wastes the day
Valid SQL can still answer the wrong question
Some days you only show up. Don’t fake a deep dive
Next 70 days I’m measuring: → one pipeline I can demo (source → S3 → transform → table) → SQL 50 finished → Python in the mix → infra I can rebuild from a template → checks on the data, not just “the query ran”
30/100 ✅
Still building in public.
#DataEngineering #AWS #SQL #LearningInPublic #100DaysOfLearning
Awwal Adepoju retweeted
Dont sleep on this !
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What happens when your database saves a transaction, but the event that should follow never gets sent? 👀
Imagine transferring $10,000, the database updates, and then the application crashes before confirming the transaction.
Now what?
I've been exploring a backend pattern that helps solve this problem, and it taught me something important about building reliable systems.
🧵👇🏽
5/6 — Building for scale
I also explored why connection pooling matters when an API handles more traffic.
My notes covered a target of 25,000+ events per second and the importance of controlling database connection overhead.
I also compared backend options:
→ Python/FastAPI: rapid development, validation and ML integration.
→ Go: concurrency and simplicity.
→ Rust: performance and memory safety.
Different tools, different trade-offs. The right choice depends on the system you're building.
6/6 — My biggest takeaway
Backend engineering isn't just about making an endpoint return 200 OK.
It's about making sure data stays consistent when things fail, events can be retried, and the system can handle growth.
I'm still learning, but I'm beginning to appreciate how much engineering happens behind a seemingly simple API.
One lesson at a time. 🤝🏽🚀
What backend concept took you a while to understand?
#100DaysOfDataEngineering #FastAPI #BackendDevelopment
Day 33/100 — Learning Data Engineering 🔧
Been exploring FastAPI, and this time, I didn't just stop at watching a lesson. 👀
I worked through building an API, learned how Pydantic helps validate incoming data, explored automatic API docs, and deployed my project to Render.
And seeing that “Deploy succeeded” message? Small win, but it felt good. 😂🚀
Still figuring things out, still learning by building.
One step at a time. 🤝🏽
#100DaysOfDataEngineering #Python #FastAPI
I've started exploring FastAPI via @hyperknow_ai , and I'm excited to see where this goes. 👀🐍
I've been learning more about backend development lately, and I want to understand what happens behind the scenes when an application receives a request, processes it, and sends a response.
Not just writing code that works, but understanding why it works.
Let's see what I build. 🚀
The tech industry will humble you every single day. 😂
You can spend hours understanding one concept, open X, and discover 5 new technologies you've never heard of.
My current strategy?
Learn the fundamentals. Build things. Stay curious. Repeat.
We can't learn everything, but we can keep learning. 🫡
One thing I'm learning on this journey:
You don't have to understand everything at once.
Data Engineering, backend development, AI/ML… there's a LOT to learn. 😭
I'm trying to focus on understanding the fundamentals, building small things, and getting a little better each time.
One step at a time. 🤝🏽🚀
Heyyy X! 👋🏽😭
Been a little quiet on here for a week, but we're back!
Still learning, still building, still figuring things out one step at a time.
Currently exploring Data Engineering, backend development, and AI/ML.
The goal hasn't changed: keep learning, build real things, and share the journey.
We moveee 🚀🤝🏽
Been watching Raqim come together, and it’s finally live 🚀
If you’re building with AI agents or interested in reliable, auditable agent systems, you should definitely check this out.
Go try Raqim and see what you can build with it 👇
Observability alone can become a crime-scene camera.
It can show you exactly what an AI agent did. But a detailed trace is not the same thing as a policy boundary that stops the action.
Imagine an autonomous AML agent is manipulated into attempting a $500,000 transfer.
The trace may tell you exactly what happened.
I wanted infrastructure that could intervene earlier.
So I built Raqim (رَقِيم): an open-source execution-integrity substrate and cryptographic flight recorder for autonomous AI agents, built in Rust.
This 51-second demo shows a prompt-injection scenario being interdicted and a 7-step AML execution branching into a counterfactual timeline. 👇
Day 31 & 32/100 — Learning Data Engineering 🔧
Day 31 was honestly a quiet one. Didn’t really get much learning done.
But Day 32? I explored HyperKnow AI and wow… I genuinely enjoyed the experience.
The learning experience is probably one of the best I’ve used so far, if not the best. 😭🔥
I really wanted to go deeper and explore more, but unfortunately I hit the usage limit before I could go as far as I wanted.
Still, I learned a lot and I’m grateful I got to experience it.
Big shoutout to @leslie_rh7 and the @hyperknow_ai team for building this. 🤝🏽
Alhamdulillah for the progress, even when it’s not as much as planned.
32/100 ✅
The shift from AI giving you answers to AI actually helping you understand is interesting.
Excited to see what @hyperknow_ai is building. 🚀
Congrats Leslie and the team! 🎉
Introducing @hyperknow_ai: a new way to learn.
The AI professor that turns any learning goal into a 1-on-1, interactive and systematic course.
While all other AIs are rushing to replace your thinking,
we raised $1M to bring back that simple excitement of understanding something for yourself.
Give Hyperknow a topic, a textbook, or anything you’ve struggled to understand before.
Watch it turn your curiosity into a personalized course, with structured units, lessons, practice, and even hands-on projects, then walk you through it on an interactive whiteboard that feels like having your own professor beside you.
More than 100k learners have already explored new worlds with Hyperknow.
Now it's your turn.
Tech is moving so fast that “I’ll learn this tool later” is starting to sound dangerous 😂
AI, cloud, robotics, cybersecurity, chips…
You look away for one week and there’s a new acronym to learn. 😭
At this point, I’m just trying to understand the fundamentals and enjoy the ride. 🫡
