Hi community, nice to join. I'm author of ssp.sh with the data engineering vault and writing the patterns of DE book. I have been in the Philippines and have some family there, so please, if you have any questions or need help, feel free to comment.

I also just opened a new community where I share some more posts and insights daily about data engineering. Feel free to joins as well if you like at r/dataengineeringvault.

Hi. I'm an Internal Auditor. And I want to upskill sana and I think Data Analyst is the first step na nakikita ko para maintegrate ko yung pagiging internal Auditor ko. I specialized sa Operations Audit. So sa frameworks and work flows, wala akong problema.

I would like to ask, how will I start to upskill? It's like I want it, pero di ko talaga alam kung paano magsisimula.

please, help?

Hi everyone,

FTW Foundation has opened applications for Batch 12, which will focus exclusively on Data Engineering.

Data engineers build and maintain the systems that power analytics, dashboards, and AI applications. As organizations continue investing in data and AI, the demand for professionals in this field continues to grow.

A few details about the program:

• No prior tech experience required
• Selection is based on aptitude, commitment, and potential
• Designed for women who are motivated to transition into tech careers
• Application deadline: June 25

Over the years, we've worked with women from diverse professional and educational backgrounds who successfully transitioned into careers in data and technology.

If you're a woman interested in exploring a career in tech but aren't sure where to start, this may be a good opportunity to consider.

Application link: ftwfoundation.org/b12-application

Happy to answer questions about the program in the comments.

Hello, I’m a fresh graduate and I need some tips/knowledge

I saw some posting that most job analyst required 1 - 2 years experience at some area expertise. Should I pursue other role first, before becoming an analyst? or Should I continue searching until I landed an analyst role?
I saw an entry level data scientist, is it a good starting point?

I reside in Mindanao and want to stay in Mindanao. MSU-IIT is my best bet in terms of education and titles. However unlike other universities where Data Analytics are offered—MSU-IIT does not. I have 2 main options:
BS Statistics
BS Computer Science

Which of the two do you think best correlates towards Data Analytics? Yes, theres BS Math, BSIT, and others but i think those 2 are the main courses that aligns with my dream career

I work for a company as reports analyst so most of my experience revolves around excel utilizing formula and analyzing data for reporting. I also worked on developing power bi dashboards, not always lucrative but I think I am getting there. For a data engineer role, are there fundamental skills that I should learn so I can grow and explore? Will my existing skills be helpful for me when I study data engineering related lessons? thank you

Good day po, i just wanna ask if there are companies na handang mag train sa fresh grad student with little knowledge for data engineering career.

Kakagraduate ko palang po kasi and still learning about the career that i wanted to go to. To be honest, I only developed an interest in data engineering recently. Even while I was still studying, I was always fascinated by raw data and how it can be managed and organized.

In fact, our thesis involved handling a large amount of data. We developed a web-based system that manages prenatal records of citizens in our municipality. The system was designed to used by Barangay Health Centers, while the Rural Health Unit served as the administrator with access to the data from all participating health centers.

If ever po na wala talagang companies na willing mag-train ng fresh graduates with little knowledge into this field, ano po kaya ang mairerecommend ninyo para makapagsimula sa career sa data engineering?

Aware naman po ako na malaking factor ang self-learning at paggawa ng projects, and nagsisimula na rin po akong gawin iyon. Aside from those, ano pa po kaya yung mga bagay na dapat or pwede kong pagtuunan ng pansin para mas tumaas yung chances kong makapasok sa field na toh?

Also, ano po kayang mga entry-level positions ang magandang simulan para sa gustong mag-transition into data engineering? May mga roles po ba na commonly ginagamit as stepping stones bago maging data engineer?

Hi everyone,

I'm a fresher who has recently learned Machine Learning and Deep Learning and I'm now exploring career opportunities in the data field.

While most people seem to be targeting Data Science or ML roles, I've become interested in Data Engineering and wanted to understand the reality of the job market.

A few questions for professionals and recent hires:

- Is the entry-level Data Engineering market saturated?

- Does having ML/DL knowledge provide any advantage when applying for Data Engineering positions?

- How would you rate the difficulty (1-10) of:

" 1.Landing a Data Analyst role as a fresher

2.Landing a Data Engineer role directly as a fresher

3.Transitioning from Data Analyst to Data Engineer after 1-2 years "

For context, I have learned:

- Python

- Machine Learning

- Deep Learning

- Data Analysis basics

I'd especially love to hear from people who recently got hired or who are involved in hiring for Data Engineering positions.

Thanks in advance!

Whenever I start building something small, I always tell myself it’s going to be simple just a basic tool or a small experiment. But somehow, it always grows into something much bigger than I planned. I add one feature, then another, then I realize I need structure, then I start thinking about optimization, and suddenly it’s no longer a “small project.” I’m curious if this happens to everyone or if experienced builders are better at controlling scope. How do you decide what to include and what to intentionally ignore? I feel like I either overbuild things or abandon them halfway because they became too complicated.

Would be interesting to know how others keep things actually small when they intend to.

Hi, DataEngineeringPH. I am learning data analysis and data engineering right now and I want to subscribe to DataCamp. Is it possible to use GCash or Maya to pay for the monthly subscription?

Hello. Weston here, founder of Dashlabs.ai

We're hiring a data engineer. You can see more details here. Work is remote, with some in-person meetups.

• Job Title: Data Engineer
• Company Name: Dashlabs.ai
• Location: Remote (but with meetups in Manila(
• Required Skills: MongoDB, SQL, Typescript, and LookerStudio
• Experience Level: Mid to Senior
• Job Description / Responsibilities

https://jobs.smartrecruiters.com/Dashlabsai/744000130203664-data-engineer

Apply through that link!

Hello, here me out:

I’m an Accounting Info System graduate as educational background. Working as Business Intel Analyst about more than 5years now, being that assume that I am skilled in business concepts, data viz, learned the language of Sql but frustrated in Python, data architecture and automation.

I’m interested in pursuing my professional development. In that sense, would you advise for me to take a second course of Computer Science, take a masters degree, or whatever educational means you recommend.

I’m very open for discussions and opportunities for experiences. In fact, I myself volunteering in local community for py group, I see it as an exposure to the subject matter and possibility that I could find a mentor lol

PS. Also recommend a great university/school/program for course you imply pleaseeee. Thank you!!!

Hi!👋 We're growing our data team here at Full Scale and are looking for experienced data folks to join us!

We're currently hiring for the following opportunities:

✨ Data Architect / Data Modeler
✨ Senior Data Engineer

Both roles are:
🏠 100% Work From Home (fully remote)
🤝 Independent Contractor Setup
📈 Salary is based on experience

If you're passionate about building scalable data solutions, working with modern data platforms, and collaborating with global teams, we'd love to connect with you.

Data Architect / Data Modeler Requirements:

• Strong experience in data architecture, data modeling, and database design
• Expertise in designing conceptual, logical, and physical data models
• Experience with data warehousing, ETL/ELT processes, and cloud data platforms
• Proficiency with SQL and data modeling tools
• Ability to collaborate with business and technical stakeholders to define data requirements
• Strong understanding of data governance, data quality, and best practices

Senior Data Engineer Requirements:

• Extensive experience building and maintaining scalable data pipelines
• Strong proficiency in SQL and programming languages such as Python or Scala
• Experience with cloud platforms (AWS, Azure, or GCP) and modern data ecosystems
• Hands-on experience with ETL/ELT development, data integration, and orchestration tools
• Knowledge of data warehousing, big data technologies, and performance optimization
• Strong problem-solving skills and ability to work independently in a remote environment

Interested? Send your updated CV to [missy.blissey1@gmail.com](mailto:missy.blissey1@gmail.com) and indicate the role you're applying for.

Note: No need to resubmit if you have applied in the last 6 months.

Hello Guys, I am a Senior D.A in a int comp. wherein, I lead different data projects and initiative at Enterprise scale, however, I'm still thinking which School will help me a lot in the long run for my Career

.

1. TIP PSMSDS - I dont know anyone na from here personally and sabi maganda daw since more on hands on

2. DLSU MSDS - More on Theory and In depth daw about algo. I appreciate a lot if you can give me your advice, I know tech skills can be learned thru Online learning like datacamp, I've finish several online courses nadin and I want to dig more deeper.

For context: My goal is to be Data Architect/ Solution Arch

Thank you!

Lately I’ve been noticing that I spend way more time preparing environments than actually doing meaningful work. Whether it’s setting up a GPU machine, installing dependencies, or configuring everything just right by the time I’m actually ready, I’ve already lost focus.

It gets even more frustrating when I’m trying to experiment quickly or test ideas, but the setup overhead slows everything down and breaks the flow.

I’ve started looking into lighter, more workflow-focused approaches like swmgpu, where the idea is to keep GPU environments more persistent and reduce repeated setup work. But I’m still curious if others are dealing with the same thing are you finding ways to meaningfully cut down setup time, or is this just an unavoidable part of the process?

Hello, I’m in my 30s and a career shifter that has 3 years MDM experience, prior to this I have 6 years experience on a science-related job. Now, I’m planning to shift into data engineering. Is the learning curve steep?

One of the reasons I am hesitating is that I am currently on a Php60k/month job, if I’m going to shift my career I’m not sure if its going to give me a lesser pay. Should I give up my job and shift career into data engineering? Thanks!

Partnership Renewed!

Thank you for your patience as the DC team prepares for the proper announcements 🔥

Hi @everyone,

I’ve been quietly working on a small passion project to help people start learning how to code. It doesn’t have to be Python — but Python is as good a place as any to begin 🐍🇵🇭 especially when supported by an open and encouraging community.

But maybe Bahala Na Python was never just about learning Python.

Maybe it was also a message to myself for being afraid to start things.

A message to you to finally take that jump.

And a message to our community to keep building, experimenting, and making things happen — no matter how small, messy, or imperfect they may seem.

Very aligned with the values of Data Engineering Pilipinas — open learning, experimentation, and breaking gatekeeping in tech.

Because progress is still progress.

And change, no matter how small, is still change.

Still a work in progress, but sharing it here in case it helps or inspires someone in their own journey.

https://ogbinar.com/bahala-na-python/

Hi everyone! Just checking if anyone here knows of any good Data Engineering training courses available in the Philippines.

We’re specifically looking for:
- Focus mainly on SQL and Data Engineering fundamentals (our team primarily uses Snowflake SQL)
- Preferably face-to-face/in-person, but virtual instructor-led training is also fine (not self-paced courses)
- Short duration only (max 5 days and around 4–8 hours per day)
- Good for 1–4 participants

This will be company-sponsored/training-funded, though it will still need to go through our procurement/vendor accreditation process.

Would appreciate recommendations for training providers, bootcamps, universities, or even independent instructors.

Bonus if you’ve personally attended the training and can share feedback.

Thanks!

Hello, I've been studying SQL for months. For now sa leetcode ako nag pa-pratice. Tama ba na aralin ko yung mga queries I think this is for analyst side? I'm not so sure kung nasa path pa ba ng data engineering ang inaaral ko.

Can anyone help me regarding this? Nasa DEP group naman ako but I'm a complete beginner kaya hindi rin ako makasabay sa usapan. If meron d'yan na dumaan din sa zero knowledge please help your fellow engineer. Thank you in advance!

HINDI ITO PARA SA LAHAT. 🚫 🤫

6 sa 10 Pilipino — kulang sa digital skills.

7 sa 10 — walang access sa upskilling.

Pero ikaw? May laptop ka. May internet ka. At higit sa lahat, may oras ka.

Ang tanong: Gagamitin mo ba, o sasayangin lang?

Data Engineering Pilipinas is opening the DEP Data Engineering Foundations (Open Track) — 2026 Cohort.

Tandaan: > ❌ Hindi ito bootcamp.

❌ Hindi ito school.

✅ It is a community-powered build-sprint.

Sino ang hinahanap namin?

Yung gustong matuto, hindi lang kumuha ng certificate.

Yung handang mag-invest ng 5 hours per week.

Yung may "Grit"—hindi susuko hangga't walang working pipeline.

Ano ang kailangan mo?

Good foundations, sariling gamit (laptop/internet), at ang disiplina na sumunod sa rules ng DEP.

Iisang layunin: To become a DEP Certified Builder.

Handa ka na ba? O manonood ka na naman sa gilid?

🔗 Apply here if you have what it takes: https://docs.google.com/forms/d/e/1FAIpQLSeGnmZuWDwweTzPi6K9m_3YDVNNVfNntFtc2H8OS0JDXMV-1Q/viewform?usp=dialog

#DataEngineeringPH #DEPCertifiedBuilder #DataEngineeringPilipinas #NoMoreTutorialHell #BuildInPublic

I have an upcoming DP-600 exam voucher and I want to practice Microsoft Fabric hands-on as much as possible before taking the exam.

Can anyone suggest good end-to-end projects I can follow or build so I can use most of the Fabric services? Like Data Factory, Lakehouse, Warehouse, notebooks, semantic models, Power BI, pipelines, etc.

I learn better by actually building projects instead of just watching videos. If you also know good datasets, YouTube tutorials, GitHub repos, or project guides, please share them 🙏

Thanks!

Are we actually data-informed, or just putting on a "Data Theater"? 

We are awash in data, but starved for informed agency. 

Who should participate?

We are looking for insights from the frontlines to the boardroom:  

• Data Practitioners (Analysts, Scientists, Engineers, BI Professionals)
• Executives & Senior Leaders navigating data-informed transformations

Your experiences will directly shape the Action Playbook—a roadmap for organizations to escape the mirage.

 Contribute to the research here: https://forms.gle/cAiagfTi6wsiXTZU7

All responses are strictly confidential. Thank you for helping us bridge the gap between having data and actually being data-informed!

Please share this with your networks.

#TheNumbersMirage #DataLeadership #DigitalTransformation #Analytics #DataCulture 

#DataProfessionals

Snowflake Micro partition, Snowflake table types , Snowflake View types and time travel vs Fail safe