Data Science and Data Engineering Training for Scalable Data-Driven Growth.

Explore Data Science and Data Engineering training courses that help professionals manage data pipelines, prepare data for analysis, build models, and support the platforms behind analytics and AI initiatives.

Build the skills needed to make data more usable, scalable, and valuable across analytics, automation, and AI projects.

Top Data Science and Data Engineering Training

Popular Courses

Top Data Science and Engineering Training

GCPDE: Data Engineering on Google Cloud

Duration: 4-days

RM 9600

Top Data Science and Engineering Training

DP-100T01: Designing and Implementing a Data Science Solution on Azure

Duration: 4-days

RM 3000

Top Data Science and Engineering Training

AWS-DE: Data Engineering on AWS

Duration: 3

RM 5400

Top Data Science and Engineering Training

ITCA-DSF: ISACA Data Science Fundamentals Certificate

Duration: 3-days

RM 5000

Top Data Science and Engineering Training

SNOW-DS: Snowflake Data Science

Duration: 3-days

RM 13500

Top Data Science and Engineering Training

DTB-DED: Data Engineering with Databricks

Duration: 4-days

RM 6750

Interested in bespoke or team training?

Get in touch with our team or WhatsApp us

Browse all Data Engineering & Science courses

Latest Data Engineering & Science Resources

January 29, 2026,
Databricks Certified Data Engineer Associate: The Entry Ticket to the 2026 Job Market
AI & Machine Learning, Data Engineering & Science,
January 1, 1970,
Decoding Databricks Accreditations: Platform Architects, Admins, and Fundamentals
AI & Machine Learning, Data Analytics, Data Engineering & Science,

Data Engineering & Science training solutions

Our cloud training solutions empower you to deliver cloud skills at scale and hire new talent to help you fill critical gaps in your workforce.

Elevate your team's Data Engineering & Science skills

Unlock your team’s potential with cloud skills designed for real-world impact. Empower teams to optimise costs, enhance security, and drive innovation.

Data Engineering & Science apprentices

Our cloud apprenticeship programmes support organisations in hiring an upskilling talent in crucial cloud platforms, such as AWS and Microsoft Azure.

Learn with our various modalities

Our online learning platform helps learners to build cloud skills in their own time. Prepare for cloud certifications with our online course library.

Data Science and Engineering Courses by category

Trainocate brings together training from vendors such as Microsoft, Google Cloud, Databricks, AWS, and other specialist providers, covering data pipelines, data platforms, machine learning support, big data, and production-ready data workflows.

These HRD Claimable Data Science and Engineering courses help professionals build scalable technical skills, while helping organizations strengthen the data foundations needed for analytics, AI, and digital transformation.

  • AWS Certifications

  • CompTia Certification

  • Databricks Courses

  • Google Cloud Certification

  • Microsoft Certification

  • Snowflake Courses

Job Roles

Explore the most in-demand roles in Data Engineering & Science

Builds models, explores data, and generates predictive and analytical insight for business and technical use cases. PayScale lists the Malaysia average at RM54,322 per year in 2026.

Designs and manages pipelines, data movement, and processing environments that support analytics and AI workloads. PayScale lists the Malaysia average at RM55,923 per year in 2026, while Jobstreet lists a common range of RM6,050 to RM8,550 per month.

Leads large-scale pipeline, architecture, and data platform work across enterprise environments. Jobstreet’s salary page shows higher market ranges in some locations, with Kuala Lumpur listed at RM11,875 per month.

This is a location signal rather than a national average, but it shows the upside for advanced data engineering roles.

Builds and supports large-scale processing environments for structured, unstructured, and streaming data. Trainocate’s Google Cloud data engineering course specifically references designing data processing systems across these data types, reflecting the role’s relevance in current enterprise data environments.

Salary levels are commonly benchmarked alongside data engineering roles in Malaysia.

Leads data science teams, projects, and business-facing analytical initiatives. External Malaysia-focused commentary notes lead data scientist salaries can reach RM180,000 to RM300,000 per year, indicating strong demand at senior levels, though this is not a national average benchmark.

Why choose Trainocate for Data Engineering & Science

Access both platform and practitioner tracks

Trainocate’s public catalogue spans Microsoft Fabric data engineering, Google Cloud data engineering, data engineering workshops, and broader data science and big data analytics offerings.

Support AI and analytics readiness with stronger foundations

Trainocate’s broader data and AI campaign positions data capability as central to Malaysia’s digital growth, which aligns well with organizations building modern data platforms and AI readiness.

Recognized enterprise learning provider

Major IT training provider with enterprise reach, local HRD Corp relevance, and international scale through the wider Trainocate Group.

Learn more about Trainocate Data Engineering & Science

Interested in data science/engineering training and want to find out more? Trainocate helps individuals and businesses gain in-demand skills and develop greater capabilities. Here some of the most asked questions about our data science/engineering training:

It covers the skills needed to prepare data, build data pipelines, support analytics, and work with modern data platforms.

Pro Tip: Build a strong foundation in data handling and platform basics before moving into advanced engineering or modelling work.

This training is suitable for aspiring data engineers, data scientists, developers, architects, and technical professionals working with modern data platforms.

Pro Tip: Choose your learning path based on your goal. Data engineering focuses more on pipelines and platforms, while data science focuses more on models and analysis.

For many Data Science and Engineering courses, some technical background is helpful, especially for scripting, pipelines, and data platform work.

Pro Tip: If you are still new to coding, start with entry-level technical courses before moving into advanced engineering tracks.

It matters because organizations need scalable, reliable data foundations to support analytics, automation, and AI initiatives.

Pro Tip: Learn tools and concepts that are relevant to your target job role so your training leads more directly to practical outcomes.

A good first step is a fundamentals course in data platforms, data engineering, or introductory data science, depending on your career direction.

Pro Tip: Start with the area that matches your daily work or career goal, then expand into adjacent skills as you progress.

Speak to a Training Consultant

All courses are HRD Claimable.
Get in touch with our team via the form or WhatsApp us on +6011-5119 6631

Preferred mode of training
Checkboxes