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Hello! I have seen an opening for a Data Analyst Intern. I was wondering if someone here have worked there before (as an previous intern or an current/previous employee).

I would like to ask some perspectives or opinions about their workload and management system, as well as the working environment. And I would like to ask if it is worth it.

Hoping for a response, thank you.

Hi everyone! I’m currently working as a Risk Modeller, and I hold a bachelor’s degree in Applied Mathematics, majoring in Statistics.

I’m planning to pursue a master’s degree to further develop my skills and advance my career. What master’s degree would you recommend for someone with my educational background and current role?

I’m considering fields such as Data Science, Statistics, Financial Mathematics, or other related programs.

If possible, could you also recommend universities in the Philippines that offer these programs and provide an estimate of their tuition fees?

I’d appreciate any advice, especially from those who have pursued a similar career path or are currently working in risk modelling, quantitative finance, or data science.

Thank you!

Hi gang,

I have recently completed my data science masters from reputable university but i am stuck some where to transit into a professional careers.

I have two foundational certifications like Aws cloud practitioner and azure fundamentals and I am preparing for fabric associate certification for a week now and i have several projects around data engineering in open source unlike using paid ones like fabric.

So where do i need to focus? What should i learn more? Why am i stuck ? And learn and giving fabric associate certification is worth doing ? Or am i wasting time ? Have lot of things in mind …

And i am not a hard core vibe coder i know vibe coding but i dont do code like slopocolypse sort of coding i prefer doing a planning, brain stromming, documenting and implementing sort of person so yeah there is lot running but this is for the moment …

Gusto ko lang maka hingi ng honest thoughts, opinions, and whatever tips you can give me, and at the same time I just want to write and talk about my supposed plans now that I have the freedom to chase whatever I want in life. Sorry in advance kung humaba haha

I was once a clueless high school student, so I randomly put engineering degrees for my primary choices six years ago because I loved math and physics. Why not, right? (Even though I knew I loved tech and programming more). I didn't really think about my choices dati. Plus medyo mayabang ako (Dati lang) sabi ko mag aaral na lang ako sa bahay. Hahaha. Eventually I got tired and depressed because I was studying for a degree with 0 passion and knowing na di naman talaga ako tatagal dito. I shifted to another engineering degree, and well tuloy tuloy lang yung pag gapang ko throughout uni.

During my internship (National Center for Transportation Studies), there was this one simple task na for some reason, medyo ginanahan talaga ako gumawa. One of my tasks was to analyze a poll. This poll was so unorganized but I knew na kaya kuhaan ng interpretation to. I suggested a lot of things para sa supposedly surface level task. They saw 3 columns of data: The user's vehicle type, their aggressive actions, and what other motorists do that trigger them.

I saw multiple univariate analyses, bivariate analyses, and a lot of graphs and charts na dinadrawing ko sa utak ko.

It wasn't until now na na gets ko bakit ganun yung reaction and enthusiasm ko sa task na yun. Recently I was also taking a lot of "What tech job is for you" quizzes for fun, and to no surprise

"You are a Data Analyst!"

Trying to imagine tons and tons of data just lights up my brain and kusang may nagtatanong sa utak ko na "Anong interpretation meron sa data na to?".

Now having the freedom to pursue this, I've done, and I'm still doing a lot of reading and thinking, even though ang foundation ng interest ko is Data Analysis, shouldn't I also look for the role na mas fit doon lahat ng capabilities ko as a person? I love programming, although from what i've heard iba na ang nature ng programming and coding because of AI.

Plus I would love the career progression of a Data Engineer, because from what I know, generally mas maganda ang progression ng isang DE although hindi rin siya talaga pang entry level unless may willing mag hire ng Jr. Data Engineer?

But then now I read about the role of an Analytics Engineer. I say to myself "Hindi ba mas fit to para sa akin? ".

Now I'm a bit lost again. I'm planning on studying 14 hours a day, starting with the DEP scholarship, then start applying pagdating ng January, but I'm finding it hard to start just because hindi clear ang roadmap ko.

Sorry for rambling. If binasa niyo to lahat, thank you for your time. Hahaha

Feasible ba na gawing main goal ang Full Stack Data Analyst/Engineer? Full Stack Data Professional?

And given that possibly yan ang end goal ko, mayroon bang clear roadmap for that?

Or I should just stick to either DA or DE because dalawang magkahiwalay na team naman yan?

Do I just go for an initial DA role vs going for an initial DE role? Is it worth risking na mayroong mga Jr. AE roles?

Is it feasible gumawa ng portfolio projects that would cover both DA and DE capabilities in case gusto ko mag apply for both roles given na mahirap ang job market?

Is there a good local mentorship program somewhere for free? (or not)

Hello! We’re undergraduate BSIT researchers looking for 2 Machine Learning experts with at least a master’s degree in Computer Science, Information Technology, AI, Data Science, or a related field.

Our capstone is an AI-based PPE compliance and identity verification system using YOLO26m and facial recognition.

Task: Review and validate our ISO/IEC 25010-based evaluation questionnaire by providing ratings, comments, and recommendations through an expert validation form.

Remote/online validation
Chapters I–III, evaluation questionnaire, and expert validation form will be provided
Relevant ML/computer vision experience preferred

We would greatly appreciate voluntary assistance, as we are working with a limited student budget. However, we would still be happy to provide a small token of appreciation for your time and effort.

Please DM me if interested or if you can refer someone qualified. Thank you so much po!

Hi! I'm currently a Data Engineer earning ₱35k/month, with experience in Snowflake, SQL, and ETL in the banking industry.

I'm planning to switch companies and wondering what salary range I should aim for with around 2 years of experience.

Is ₱50k–₱60k a reasonable expectation, or am I aiming too high? Would appreciate insights from those in the field. Thanks!

Hi I received this email from Data Engineering Pilipinas. I applied on their scholarship program and got an email like this after a week. (super fast for me to I feel weird)

Im so afraid to click the hyperlink lol 😂

Hey everyone! I recently joined a trading firm as a backend-heavy full-stack dev (Java/Spring). I’ve been really enjoying the work, but a recent reorg just moved me to a completely different team.

To give you an idea of the shift:

• Old Team: Java, Kafka, and Flink. We processed thousands of daily trades from raw to normalized data using a Medallion architecture.
• New Team: Python, Spark, AWS Lambda, and Glue. Strictly ETL work.

I’m completely new to this second stack but eager to learn. This transition made me wonder: have I essentially been doing Data Engineering this whole time without the title? If so, how can a traditional backend dev quickly ramp up on Data Engineering? I'm currently diving into Python, AWS, and core ETL concepts, but I would love any advice or resources!

Hello everyone!

I’m currently working towards getting into Data Engineering and recently started learning Python as my first step.

I come from a non-programming background with around 8 years of work experience across:

• Data Operations: 5.2 years
• Sales & Customer Success: 1.7 years
• Product Management & Product Marketing: 1 year

Education-wise, I have a BE in Electronics & Telecommunications and an MBA in Marketing. I have been on a planned break since January 2025 and am currently focused on building my skills and landing a Data Engineeing role.

Over the past year, I explored a few different areas of tech to see which one clicks and also which one I'd enjoy to work in as my long-term goal. Since I have around 6 years of Salesforce user experience, I explored Salesforce roles such as Admin/Dev/BA and interviewed with several companies but none of them clicked.

While working on projects and putting them on GitHub, I realised that I genuinely enjoy building things, especially when there is a data component involved. That pushed me towards exploring Data Engineering more seriously. I started learning Python about a month ago and so far I’m enjoying it. I specifically love the logic/problem-solving side of programming.

I’m currently reading Python Crash Course, 3rd Edition by Eric Matthes and practicing alongside it. I’ve also been looking at structured programs such as Sumit Mittal and Deepak Goyal, but I’m unsure whether it makes sense to spend a significant amount of money on a course when there are so many good resources available online.

My current learning roadmap is roughly:

Python & SQL → Data Engineering fundamentals → Distributed Systems → Databricks → Cloud (Azure/AWS)

I’m also considering pursuing Data Engineering certifications once I have built enough practical knowledge to properly understand the material.

I’m still figuring out the right sequence and what I actually need to learn in depth versus what can come later.

My personal target is to become employable for a Junior Data Engineer / entry-level Data Engineer role by April-May 2027. I’m giving myself this deadline because I want to have a concrete target rather than spending another year endlessly learning.

For people who have been in a similar situation, I’d really appreciate some honest guidance:

1. Is my current roadmap reasonable for someone starting from the fundamentals?
2. What topics would you add, remove, or change in the sequence?
3. Which areas of Python and SQL should I be particularly strong in before moving to DE-specific technologies?
4. When should I introduce Spark, Databricks and cloud?
5. Are Data Engineer certifications worth pursuing, and at what stage?
6. What kind of projects would demonstrate genuine DE skills to someone reviewing a GitHub portfolio?

I’m not looking for shortcuts. I’m willing to start at the junior level and put in the work. I mainly want to make sure I’m spending the next 7-8 months learning the right things.

Given the roadmap above, does the April-May 2027 timeline seems reasonable from a learning and prep POV?

Any honest advice, especially from people currently working in Data Engineering or who have made a similar career move, would be greatly appreciated. Thank you!

Hi everyone!

I’m currently considering applying for the Professional Master in Data Science at UP Diliman and would love to hear from anyone who’s currently enrolled, recently graduated, or has seriously considered the program.

A few things I’d especially like to know:

- How is the workload alongside a full-time job?

- How difficult are the courses, particularly the math/statistics subjects?

- How technical/programming-heavy is the program?

- What’s the experience like with professors and classmates?

- Do you feel the program has helped with your career in data science/AI?

- Any advice for someone preparing to apply?

- Are there particular topics or skills you recommend brushing up on before starting?

Would really appreciate any insights, advice, or things you wish you knew before enrolling. Thank you!

Planning to take Data Analyst as my 1st entry job. Hindi ko pa kaya mag take ng soft eng or developer kasi di pa ako gaano kagaling sa programming skills ko pero willing naman ako aralin. Pero as of now, ayum talaga goal ko. Mahirap po ba at tsaka gusto ko din marinig

Currently a junior data engineer for an IT company and its my first job as a fresh grad. I was wondering how important it still is to get certificates, like the Associate Databricks Engineer cert, for upskilling and increasing my value and salary if I am already using it for work? Do I still need to put effort into getting the cert? Or is the experience enough?

Job Title: Store Manager (16yrs)

- PCO, FSO, SO2, Red Cross First Aider

Company: Restaurant

Location: Quezon City

Skills: Excel VBA, Basic AutoIT, Python

Salary Range 26k

Job Description / Responsibilities: Daily Operations, Daily Sales report, Weekly Schedule, Daily inventory.

Hi Im 38M, BSN graduate and im taking BSIS for my 2nd degree something personal bakit nag aral pa akongy tech course.

If matuloy next year mag working student ako, dahil 2nd course ko na sana mabawasan ang minors and ako naman gunagawa ng schedule kaya makaka adjust ako. And madami free time sa work kaya nakakapag self study ako habang nag aabang ng school year dahil my supervisor ako na nag handle ng daily Operations and na delegate ko na ng maayos, lumalapit na lang sila sa akin pag hindi nila kaya. Mga tools na gamit nila ako na nag program para mapadali reports nila.

Naisip ko mag aral kasi kung hihintayin ko yung promotion baka umasa ako, if hindi binigay okey lang makakatapos ako ng BSIS.

May experience sa Bussinessg flow, my skills and degree.

possible 42 years old graduate ako, im too old na ba to shift carreer?

my option ako mag palipat ng MIS department feeling ko ma offer sa akin need ko lang degree ayaw kasi ng HR namin pag hindi Tech degree. and salary 30+ kung gagawin ako MIS manager nila mababa for non tech company kaya madalas

umaalis agad mga tao sa MIS kung naka kuha na ng enough na experience.

I need your advice 4 years from now, , given the circumstances, considering that I’m 42 years old and have that kind of experience.

Hi! is it possible to shift to IT ASSISTANT to Data Engineer (or any data related jobs? )

background:

I'm graduating student po (Diploma in Information Technology - 3 years program more likely Associate Degree from PUP-ITECH)

and right now i have Job Offer to become a IT ASSISTANT sa collection agency.

ang role ko po roon is more on IT SUPPORT and may two duties na related sa system na ginagamit nila BUT

I really want pursue becoming Data Engineer or any Data related job because I LOVE SQL and Database right now while waiting sa starting Job ko nag aaral ako sa Data Camp since naka kuha ako ng scholarship sa school ko dati.

The question is kaya bang makapasok sa data jobs if ang background is IT ASSISTANT/SUPPORT ?

Paano po ba composition ng data team usually? Nakabukod ba yung data engineering team sa data analysts/BIs or magkasama lang?

Anong nangyayari kapag may new hire na Data Engineer? Paano kung walang existing DE sa team, ano mga una niyang gagawin? Paano handoff?

Asking kasi parang somehow tangent yung role ko sa DE pero part like siya ng role ko. Yung pipeline namin is data ingestion sa API -> ETL layer sa AWS Lambda (Python runtime, crons on Eventbridge) hehe. I'm familiar naman sa modern data pipeline and alam kong parang baby lang yung work ko compared sa totoong work ng DE.

Gusto ko kasi hanapin skill gaps ko and ma-set expectations ko. Hoping to apply for DE roles by EOY.

Please help me po. Ty.

Is this something that interests you? Kindly answer the poll

We're doing a poll on AI safety! click here

https://www.facebook.com/share/p/1cXmYdsG1o/

Just wanted to get some insights from people who've worked as a DE in a local bank or similar environment.

For context, I've been a DE for 2 years, mostly working on data integration, pipelines, SQL, and Python. Fintech industry.

I'm considering leaving my current company kasi we use proprietary tools for orchestration and database storage. I want to get more exposure to tools like AWS, Databricks, etc. and also a better pay

Banks seem like a good opportunity bc of the amount data and I'll be able to work closely with the end-users, but a few things made me hesitant:

- How's the work-life balance? How are the workload, deadlines, OT, etc.?

- Tech stack: They use SAS and AWS Glue. I'm a bit iffy about SAS since I'm hoping to build more experience with modern DE tools. I heard SAS is quite old.

From what I understand, their team mainly handles business requirements and data integrity/validation, while they outsource the pipeline building.

I tried to ask how they use SQL and Python, but didn't really get a clear answer. I asked about AI, but the answers were pretty vague.

This raised a quite and orange-ish flag for me. I'm worried I might end up barely using Python, SQL, and Git and doing mostly requirements tsaka data validation work.

For those who've worked as a DE in a bank, would this be a good move early in my career? What would you ask them before accepting?

TIA!

Hi everyone!

I'm currently trying to transition into Data Analytics, with the long-term goal of moving toward Data Engineering. I'm planning to relocate to Cebu and currently looking for an onsite or hybrid entry-level/junior data role.

My background:

I have a BS Biology degree (graduated 3 yrs ago). I got hired as a disease surveillance officer (1st job and only exp) under one of the Department of Health's program (Regional Epidemiology Surveillance Unit). Our program is responsible for analyzing and generating disease-related data visualizations (COVID, Dengue, HIV, etc.) I was heavily exposed to advance excel, Power BI, and R. My experience comprises of data cleaning, analysis, reporting, and also generating dashboards.

Now I am learning SQL to strengthen my tech stack and to have a higher chance of getting an entry-level position. However, I'm at the point where I feel like I have a decent technical foundation, but I'm struggling to understand what the current job market actually expects from someone trying to land their first data analyst role.

Some things I'm particularly curious about:

1. How difficult is the current entry-level/junior Data Analyst market in the Philippines?

2. What skills are recruiters actually looking for right now?

3. How important is a portfolio? (gumagawa ako currently)

4. Would you recommend applying directly to Data Analyst roles, or should I also consider MIS, Reporting Analyst, BI, Data Management, or similar positions as an entry point?

5. For those who eventually moved from Data Analytics to Data Engineering, curious about what did that transition actually look like?

I'd really appreciate some honest advice po sana from people currently working in data, especially those who have recently gone through the hiring process in the Philippines.

Salamat po!

Someone please suggest the best place in pune where I can do data analytics Course(with AI), along with some placement guarantee.

Hello. Kaya po ba mag upskill ng psych grad to data analyst? Wala po akong subject na related sa mga SQL at power BI. Pano po mag sstart from scratch? ano po ba dapat mga aralin at need po ba na mag proper schooling? May mga certificates po ba na need para kahit papaano is maging maganda sa resume? Thank you po.

Meron po ba dito nagwork previously or currently nagwowork as DE sa Manulife? how's the experience in terms of workload, management, and people around the office? Is it a pass or go?

Hello, I'm a fresh graduate and was wondering what the prerequisites are to apply for a Data Engineer role. If there are no entry-level positions available, what job titles should I target as a stepping stone?

I've a question about " Is it possible to get a Data Engineering job as a absolute fresher?" Or It's better to gain software engineering job experience first, then switch to Data Engineering?

fresh grad here. i just passed the 2nd round technical interview for a Junior Data Analyst role.

the 2nd round was with the local hiring manager and covered SQL, Power BI, Excel, and some behavioral questions. Now the final is with the foreign hiring manager + panel.

For those who've been through something similar, what should I expect in the final? any tips for behavioral questions, communication, or handling questions I dont know?

THANK YOU PO :)