Data Guru

I'm a beast

AI/Data engineering

[Sahil @sahill_og]

Everyone: "Study AI & ML, it pays so well"

Me after trying to understand the math behind it:

[John Doe @StanleyMasinde_]

Data engineering yes. Data analytics no!

SDEs have built things like Elastic Search just to avoid doing manual data stuff.

If you have been a Fullstack in a small org, you’ve been asked to help with preparing data here and there. I hated that kind of work. But it made me appreciate good db designs.

[Caleb Jephunneh @Code4jeph]

i just need to lock in
i just need to lock in
i just need to lock in
i just need to lock in
i just need to lock in
i just need to lock in
i just need to lock in
i just need to lock in
i just need to lock in
i just need to lock in
i just need to lock in

[Certified Roadman @SteeNyamu]

Drove up north yesterday, proudly sponsored by Cashia ( Cashia | Kenya's Digital Payments Platform | Send & Receive Money https://t.co/MxrmwfUp2L ) and Empire FX ( EmpireFX – Build Your Empire https://t.co/GEa7sijaJe )
A solid 16 hour drive on the most jawbreaking roads!

[anushka @anushkag319]

Which one should I buy first???
I am a little confused, any suggestions?

[Son Of Anarchy @__QlintDwayne]

Absolute scenes from last night

[Data Guru @mochache__]

Created an end-to-end Cancer Genomics ML pipeline for processing copy number variation data, training regression models, and serving predictions through a Flask web interface with Airflow-compatible ETL workflows.

[J.A Olaoye @JA_Olaoye]

Your tool Box should be equipped as follows as you work towards building as senior Data Engineer.

Data Engineer
│
├── 1. Programming → Build
│ ├── Python
│ ├── SQL
│ └── Scala
│
├── 2. Processing → Transform
│ ├── Apache Spark
│ ├── Databricks
│ └── Apache Flink
│
├── 3. Orchestration → Schedule
│ ├── Apache Airflow
│ ├── Prefect
│ └── Dagster
│
├── 4. Cloud → Host
│ ├── AWS
│ ├── Azure
│ └── Google Cloud Platform (GCP)
│
├── 5. Warehousing → Store
│ ├── Snowflake
│ ├── BigQuery
│ └── Amazon Redshift
│
├── 6. Streaming → Real-time
│ ├── Apache Kafka
│ ├── Amazon Kinesis
│ └── Pub/Sub
│
├── 7. Lakehouse → Modern Storage
│ ├── Delta Lake
│ ├── Apache Iceberg
│ └── Apache Hudi
│
├── 8. DevOps → Deploy & Scale
│ ├── Docker
│ ├── Kubernetes
│ └── Terraform
│
├── 9. Data Quality → Trust
│ ├── Great Expectations
│ ├── dbt
│ └── Monitoring & Validation
│
└── 10. Architecture → Design Everything
├── Data Modeling
├── Pipeline Design
└── System Architecture

[DataVidhya @thedatavidhya]

> Two Data Engineers.
Same experience. Same resume.

- One gets interview calls every week. The other can’t even clear the first round.

The difference?

→ One adapted to the 2026 Data Engineering stack
→ The other is still following the old playbook

In this video I talked about:

→ Why ETL is slowly getting replaced by ELT
→ Why DBT is everywhere now
→ Why Lakehouse architecture matters
→ Why learning 50 tools is useless without fundamentals
→ How AI is changing Data Engineering workflows
→ The one skill most Data Engineers still lack

And no, it’s not coding.

[Microsoft Learn @MicrosoftLearn]

Not all data is created equal, especially in data engineering and analytics.

There are three main ways to classify it:
1. Structured data → Neat and predictable, like a perfectly organized spreadsheet
2. Semi-structured data → Has a flexible structure where fields can differ, like online forms or survey responses
3. Unstructured data → Anything free-form like documents, images, audio, or video

[Edison @CodeEdison]

Here are tech jobs that will stay relevant in the AI era:

•AI/ML Engineer
• Data Engineer
• Backend Developer
• Full-Stack Developer
• DevOps Engineer
• Cloud Engineer (AWS, Azure, GCP)
• Cybersecurity Engineer
• AI Product Manager
• Prompt Engineer / AI Specialist
• Robotics Engineer
• Embedded Systems Engineer
• Blockchain Developer
• Site Reliability Engineer (SRE)
• Software Architect
• Network Engineer

These are Jobs that involve building, managing, or securing systems won’t disappear they’ll evolve with AI.

[Godsent Ndoma @Godsent_Ogar]

We don’t talk enough about the Data Analyst to Data Engineer pipeline

[Machiavelli Bot @UnmodernmanBot]

The fastest way to get disrespected is to treat access to you like it is free. Attention is currency. When you give it to disrespect, you reward the behavior you hate. When you withdraw it calmly, you teach the room your price. Status is not demanded, it is enforced through what you stop tolerating.

[ehime ora @ehimeora]

You can start over on a random Wednesday and decide you want more out of life.

[Nicholas Fabiano, MD @NTFabiano]

Your partner's cognitive function may contagiously influence yours over the years.

[99 Majik @99Majik]

If you want to go far in life, master being bored, silent, and alone.

[Nik Shevchenko @kodjima33]

Spent 4 months and built Omi for Desktop, your life architect

It sees your screen, hears your conversations and tells you what to do next

It’s like having a second brain that actually pays attention

Open source, local, link below

[The Shift Journal @TheShiftJournal]

“A man who has read a thousand books is armed for life; a man who has read none is easy prey. The man who has read a thousand books has lived a thousand lives. He has seen cities he has never visited, spoken to men who died centuries ago, and walked in worlds that no longer exist. Reading does not merely inform him; it enlarges him. It stretches the boundaries of his own experience until he becomes something more than himself.”

-G. K. Chesterton

[Quant Beckman @quantbeckman]

The method’s core objects depend on the prior Sharpe ratio and the bond-vs-stock prior weighting. The authors even say they highlight the 80% prior because it tends to yield the best out-of-sample performance 🤨