DEP Survey 2026 (Back to dashboard)

DEP State of the Community Survey Summary

DEP Survey 2026

n = 1,861 respondents · 95% confidence · 96.6% Philippines-based

Headlines

• AI adoption is now mainstream. 74.4% use AI tools daily or weekly for work; 80.8% do so for study. Students lead on AI study frequency (65.8% daily), signaling a generation that has already internalized AI as a default tool.
• SQL, Python and Excel are the core tools. Majority of professionals use SQL 71.1%, Python 60.0% and Excel 70.4%.
• About half of Data Professionals use the cloud. AWS (45.2%) and Azure (49.1%) dominate. Slightly higher among DEs - AWS (53.5%) and Azure (52.1%). Also present among DAs: Azure 37.0%, AWS 36.1%, GCP 36.1%.
• LinkedIn dominates the job search platforms (74.4%).
• Salary challenge is real. 48.3% of employed members earn ₱35,000/month or below. Career Shifters are disproportionately concentrated here (66.5%). Data Engineers are more likely to earn ₱100k+ (39.0%) than Data Analysts (15.5%).
• Hardware could be a barrier for heavy workloads. 84.5% rely on a laptop as primary device. Only 5.8% have access to a workstation. For cloud and heavy computation workloads, this creates a meaningful bottleneck — especially for students.
• DEP DataCamp scholarships are the community's anchor program. 89.6% of respondents have engaged with the DataCamp scholarship — the highest awareness of any DEP initiative by a wide margin.
• Job satisfaction is salary-driven, not role-driven. High earners (₱100k+) show satisfaction scores of 8-10 at 70.9%; those at ₱35k and below at 17.7%. Career Shifters exhibit the lowest satisfaction profile across all segments (69.0% at 1-5 scores).

The Data Engineering Pilipinas Community

DEP surveyed 1,861 community members in early 2026 — the most comprehensive picture of the Philippine data professionals, students and career shifters to date. The community is technically ambitious, AI-native, and has high aspirations, both career and salary-wise, with a clear thirst for continued learning and high loyalty to DEP.

Community snapshot

Strategic implication

Segment 01

Students & Job Seekers

The data role landscape

The data profession in the Philippines has many clusters. The survey reveals at least seven primary role clusters that students can map to their coursework and portfolios:

• Data Analysis & Insights (27.8% of employed respondents) — the largest single role cluster. Core tools: Excel, Power BI, SQL, Python, DAX.
• Data Engineering (11.1%) — the higher-earning segment. 39% earn ₱100k+; driven by 24.4% earning ₱125k-₱250k. Core tools: Python, SQL, cloud platforms, Git.
• Software Engineering (7.8%) — overlaps with DE in toolset; acts as a common bridge role.
• IT Operations (7.7%) - work adjacent to data. These roles offer entry points for on-the-job skill-building.
• Education, Research, Consulting (combined ~7%) — niche roles that reward depth over breadth.

What increases odds of getting hired

Based on tools, learning platforms, and job-search methods used by currently employed data professionals

Technical skills that signal readiness

• SQL (71.1% of Professionals use it) — the single most important foundational skill. No debate.
• Python (60.0% of Professionals) — mandatory for DE, used by half of DA.
• Microsoft Power BI (56.0% among BI tools) — the dominant BI tool in Philippine enterprise.
• Microsoft Excel (71.3%) —fluency expected.
• DAX (20.6% of Professionals vs. 2.2% of Students) — a meaningful differentiator for Data Analyst roles. The gap signals a high-value upskill opportunity.

Job search platforms used by Professionals

• LinkedIn (74.4%)— the dominant channel by a wide margin, sig higher than 56.1 % of Career Shifters. Indicated Action: Build a complete, project-rich profile.
• Jobstreet (34.8%) and Indeed (26.4%) — secondary channels worth monitoring for volume.

Implications for Job Search

Salary ranges to expect

Data Engineering Attracts Premium Compensation

Google Sheets vs. Excel — is Google Sheets enough?

• 71.3% of all respondents use Microsoft Excel; 70.4% of Professionals specifically.
• 49.7% use Google Sheets — it is embedded in workflow, but overwhelmingly alongside Excel, not instead of it.
• The analysis of tool combinations shows Google Sheets and Excel are most commonly used together. Professionals who only use Google Sheets are a small minority.

Google Sheets

Digital Learning Tools Used by Students

Less utilized free resources

The significance of AI for Students

• 65.8% of Students use AI tools daily for study — significantly higher than Professionals (54.9%) or Career Shifters (53.1%). This is the most AI-native segment in the community.
• ChatGPT (86.6%), Gemini (68.2%), Copilot (45.2%), and Claude (42.8%) are the dominant tools. Students over-index on GitHub Copilot (24.7% vs. 13.6% Seeking work, 5.2% Career Shifters) and Blackbox (8.7%), indicating practical coding assistance use.
• AI is not a productivity hack for this segment — it is the medium through which they learn.

Implication of AI Use in Students

Segment 02

Career Shifters

Top skills for Data Analysts

Based on what business intelligence tools and coding tools DA Professionals actually use vs. what Career Shifters currently have — ranked by gap size (highest ROI):

<!—dimmed-tail-->

(1.0% are both DA and Career Shifters, so this is a percentage point analysis.)

Top skills for Data Engineers

• Python (78.5% of DE Professionals) — non-negotiable. The primary programming language of data engineering in this community.
• SQL (88.6%) — more heavily used in DE than in DA. Complex queries, optimization, and stored procedures are likely expected.
• Cloud platforms (AWS 53.5%, Azure 52.1%) — near equally dominant. Both are required exposure; GCP less prevalent in DE (26.8%).
• Git/GitHub (48.8%) — version control is standard professional practice. A portfolio without GitHub is a significant gap.
• Draw.io (35.4%) — architecture diagrams are a practical DE deliverable. Proficiency signals ability to document and communicate system design.
• Jira (40.2%) — agile tooling is embedded in DE professional workflows. Familiarity matters for team integration.

Hardware guidance

• 84.5% use a laptop as their primary device. Sufficient for most DA work.
• 11.3% of DA Professionals use a workstation (vs. 0.8% of Students) — workstations become relevant as workflow complexity grows.
• For DE: 19.5% use VMs, 12.2% use workstations. DE workloads benefit from higher RAM and compute. Something to consider when upskilling.

Should DA portfolios include cloud/AI projects?

• Cloud platforms in DA: Azure 37.0%, AWS 36.1%, GCP 36.1% — present but not dominant.
• Google Looker Studio (11.8% of DA Professionals) is a pragmatic entry point combining cloud-adjacent BI with free access.
• 60.2% of DA Professionals use AI daily for work — portfolio projects demonstrating AI-assisted analysis are increasingly relevant.

Should DE portfolios include cloud/AI projects?

• AWS (53.5%) and Azure (52.1%) are near-mandatory for DE Professionals. A portfolio without a cloud project is a significant gap.
• GitHub Copilot (16.5%) and Cursor (12.7%) among DEs indicate AI-assisted coding is mainstream in DE work.
• Databricks assistant (10.1% of DE Professionals) is emerging as a specialized DE AI tool.

How relevant is content creation?

• Only 0.4% of all respondents are in content-related roles as their primary data role.
• 7.3% of respondents are willing to "regularly post content" as a volunteer activity.
• Career Shifters use Facebook more prominently for job discovery (27.0% vs. 15.2% of Professionals) — content-driven personal branding may supplement formal job search.

Content creation is not a core skill requirement for DA or DE roles. However, a monthly LinkedIn post sharing a portfolio project or insight is sufficient to maintain professional visibility — and LinkedIn remains the #1 job discovery platform at 74.4%.

AI use among Career Shifters

• Only 50.2% use AI daily for work — lower than both Professionals (65.3%) and Students (58.1%). This is a gap to close urgently.
• 15.4% use AI monthly or less often for work — significantly higher than other segments. This segment is lagging on AI adoption velocity.
• 3.4% say they do not plan to use AI — the highest refusal rate of any segment.

Cloud usage among career shifters

• Less use AWS 25.8% (45.2% Data Pros) and Azure 31.5% (49.1% Data Pros) but more use GCP at 60.7% (26.8% Data Pros).

Segment 03

Data Professionals

Salary profile

The data professional segment has a skewed salary profile: 69.5% of Professionals are in the two lower categories. The ₱75k-₱100k band is thin (9.1%), acting as a bottleneck. Getting above ₱100k requires several strategies.

Moving to the next salary band — all the tips

Tool sophistication can differentiate between bands

• ₱100k+ earners use more SQL (76.9%, sig. higher than lower 2 bands) and python (73.6%, sig. higher than other 3 bands). Bash script (16.5%) is a niche differentiator.
• Higher earners use significantly more niche or advanced BI tooling: Tableau (38.0% at ₱100k+ vs. 11.2% at ≤₱35k), Python custom tools (16.5% vs. 4.4%), Alteryx (10.1% vs. 1.5%), and Qlik Sense (8.9% vs. 0.0%). Power BI adoption is high across all bands — it is not a differentiator in itself.

Cloud platform exposure

• AWS (45.2%) and Azure (49.1%) dominate among Data Professionals. Given that more Data Professionals than Career Shifters are in the higher salary groups, Certifications in either AWS Solutions Architect or Azure Data Engineer — can correlate with upper salary bands.

How long to stay before looking for more

• The median tenure-at-current-salary sits in the 1-2 year band (27.4%) — the standard market cycle for a raise review.
• Conduct a quiet market check at the 18-month mark: apply to 2-3 roles to calibrate market rate, even if not actively leaving. Use results as leverage in an internal compensation conversation.
• If no raise in 2+ years: begin active job market exploration. The data does not support passive waiting beyond this window.

Is a side gig common?

• 22.2% of employed respondents had a side gig in the past 12 months — roughly 1 in 5. This is driven more by Software Engineers (34.5%), sig higher than DA(20.9%) or DE (18.3%).
• Side gigs are common but not the norm for this community. They are a viable income supplementation strategy.

Is a Master’s degree worth it?

• Master’s holders are 4× more common at ₱75k-₱100k (15.4%) than at ₱35k and below (3.9%).
• At ₱100k+, 18.6% hold a Master’s — disproportionately higher than the community incidence of 4.9%.
• But , 84.6% of ₱100k+ earners do NOT have a Master’s. The premium likely comes from degree + specialized depth, not degree alone.
• DA Professionals with a Master’s: 10.2% are notably higher than DEs (3.7%), suggesting academic credentials matter more in analytical/research-adjacent DA roles.

What drives job satisfaction?

In terms of work setup, Remote has the highest 8-10 satisfaction score (45.1% sig higher than Onsite 20.5%). Crossing into the ₱75k+ band and moving to a Remote set-up appear to be the drivers of satisfaction.

Placeholder for: RandomForest, LR and Lasso Results later(parked in deep-dive folder notebooks)

The "master one BI tool" advice — is it supported?

• Power BI dominates at 62.9% of Professionals — and 69.1% of DAs specifically. Power BI is the correct choice for the Philippine market.
• Excel is the next top BI tool at 58.4% of Professionals, 65.7% of DAs. Strictly speaking, it is not a BI Tool. It is widely recognized that Management often requests charts in Excel spreadsheet form, hence the Power BI feature “Export to Excel”. Some analysts solve this by including a “Table” as one of the charts, to satisfy this recurring requirement.
• Note that ₱100k+ earners show multi-tool fluency: Tableau (38.0%), Google Looker Studio (17.7%), Python custom tools (16.5%), Alteryx(10.1%), Qlik Sense (8.9%) and Grafana (8.9%). Others are even more niche.
• Google Looker Studio is growing (10.6% overall, 17.7% at ₱100k+) and benefits from free access.

The significance of AI for Mid-Career Professionals

• 65.3% use AI daily for work, higher than Career Shifters(50.2%). AI is fully integrated into workflow.
• ChatGPT (81.8%), Copilot (52.5%), Gemini (48.4%) and Claude(30.5%) are more popular. Databricks assistant (5.0%) and company AI tools (5.3%) indicate enterprise AI integration is beginning.
• AI proficiency is no longer a differentiator among Professionals — it is mainstream. The differentiator has likely shifted to AI specialization: knowing which tool to use for which data task.

Segment 04

DEP Community Leaders

The community profile — 60 seconds

• Predominantly young: 44% aged 20-24; 29.7% aged 25-29. Majority under 30(75%).
• Predominantly Filipino: 96.6% Philippines-based; 83.5% Metro Manila / BalLuzon combined.
• Talent pipeline first: 55.7% are Students or Job Seekers — not yet in data roles.
• Educated and diverse: 89.8% Bachelor's level or above; 58.5% of Career Shifters have non-computing degrees.
• AI-native: 74.4% use AI daily or weekly for work; 80.8% do so for study.
• Emerging-earners: 48.3% of employed members earn ₱35k/month or below.
• Hungry for self-improvement and advancement: Joined DEP for Upskill acquisition (83.0%), career advancement (75.3%), continued learning (78.5%).
• Appreciative of DataCamp: 89.6% have engaged with the scholarship — highest utilization of any DEP initiative.

Elevator pitch — cloud provider partnerships (Snowflake, Databricks)

Why the data supports this pitch

• 39% of DE Professionals earn ₱100k+ — cloud platforms (AWS 53.5%, Azure 52.1%) are central to that trajectory.
• Career Shifters are actively upskilling: 86.3% prioritize upskill acquisition; 62.5% are working through the decision to shift.
• Community has demonstrated platform adoption at scale: Datacamp (49.3%), Coursera (30.0%), GitHub (25.8%).
• Databricks assistant usage is emerging organically (10.1% of DEs) — partnership would accelerate and formalize this adoption.

How to engage with the community more effectively

How to help more people — beyond scholarships

• Career advancement (75.3%) — alternative mentorship programs, job boards, company partnerships. 15.1% of Professionals are willing to mentor. Explore free alternatives with specific time-bookings like ADPList so that mentors will only commit to a specific timeframe (e.g. every first Thursday of the month) and mentees book time with them (ex. (topic: Resume Review, Burning Issue at Work)
• Networking (59.4%) —continue the location-based networking meet-ups, LinkedIn cohort-building, referral threads in Discord.
• Communication skills (50.3%) — encourage more ideas to build DataMasters, a DEP Communication Skills Track in addition to Leadership Program would be distinctive and sponsor-attractive.
• "Decision to shift" support (62.5% of Shifters) — dedicated Career Shifter roadmap with DA/DE pathway + mentorship + job board.
• Hardware access — a structured laptop donation program matching corporate donors with high-engagement students costs DEP nothing and addresses a root cause of access inequality.

Self-paced learning — blueprint for high enrolment and completion

Low-hanging fruit for enrolment

• Target Students first (34.5% of community; 81.6% want upskilling). Time-rich, motivation-high, lowest switching cost.
• Job Seekers second (21.2% of community, 86.9% want upskilling) — highest motivation-to-enrol ratio. Course completion directly = job readiness.
• Use the DataCamp hook: 89.6% already engaged. Announce the self-paced program as "the bridge from DataCamp to portfolio" — frames as a next step, not a new commitment.

The completion architecture

• YouTube-first delivery: 65.8% learn via YouTube. Host modules as YouTube content; Discord threads for Q&A.
• Discord accountability cohorts: 46.9% use Discord; 66.2% of Students(56.7% JobSeekers, 16.2% Professionals, 35.1% Career Shifters). Weekly Discord check-ins are zero-cost, high-impact for completion.
• DEP- costs branded certification: shareable on LinkedIn. Directly activates career advancement motivation (75.3%).
• 4-week sprint format: Reduces drop-off risk for career-motivated learners (75.3%) by creating bounded milestones. Short cohort windows also make volunteer teaching commitments sustainable and repeatable.
• Volunteer-taught live sessions: 38.8% willing to share knowledge; 25.9% co-train. One live session per sprint creates accountability and keeps production at zero.

Set-up for Completion Success

The significance of AI for DEP Community Leaders

• Opportunity: DEP can occupy the distinctive position of teaching "AI-assisted data work done right" — integrating AI explicitly into every module: "here is the concept; here is how AI explains it; here is where AI gets it wrong; here is how a practitioner validates it."
• Volunteer sustainability: AI tools can reduce content production effort by 5-10×. Volunteer contributors can generate high-quality modules at a fraction of manual development cost. This is the AI dividend for a volunteer-run organization.

AI Strategic Use in Self-Paced Curriculum

Suggested Next Steps for DEP 2026