Professional Certificate Course in Data Engineering
This course now carries Applied Data Engineering (AI-Enabled).
Design and run the data pipelines and platforms AI depends on.
Approximately 54 live training hours; approximately 65 hours including self-paced learning, aligned with the HQ batch. For data, IT and platform engineering teams building the pipelines and platforms AI depends on.
Malaysia training provider: 360DigiTMG Sdn Bhd (MyCoID 1265527-M).
SUNY Potsdam certification pathway: Data Engineering.
HRD Corp claimable; we support the documentation.
- Approximately 54 live training hours; approximately 65 hours including self-paced learning
- 120 Hours Streaming Hours & Coursework
- 6 months Learning Management System access
- Blockchain enabled tamper-proof security certificate
- Aligned to Microsoft DP-203: Data Engineering on Azure
Academic Partners & International Accreditations
Calendar-for-Virtual Interactive Classes
Start Date
Data Engineering Course
Total Duration
4 Months
Prerequisites
- Basic programming skills
- Python knowledge (recommended)
- SQL/NoSQL experience (desired)
- Basic Linux knowledge
Data Engineering Training Overview
The significant role of Data Engineers is to focus on processing data in a way that makes it easy for them to extract meaningful value from it. In this course, explore the various skills involved in laying down a successful foundation for digital transformation and facilitates the deployment of Data Science initiatives. Learn the tools and frameworks that data engineers need today to leverage AI, machine learning, and business intelligence skills to effectively manage data.
Data Engineering skills are constantly evolving with several skills unique to their profile. Learn advanced SQL techniques along with tools like Python, Keras, Pytorch, Spyder, etc. to handle a huge amount of data and solve real-world problems faster. Gain a thorough understanding of building data pipelines and integrating them smoothly with various data structures to keep pace with big data needs and implement data science and AI initiatives in your organizations.
What is Data Engineering?
To make data-driven decisions, data has to be collected, sorted, and analyzed giving results to quality data. This process of giving insights from data to businesses using advanced analytical tools is termed Data Engineering.
Data Engineering Training Learning Outcomes
Transforming data from a raw format to attractive analytical boards is a long journey that requires a dedicated environment known as data pipelines to obtain, process, and store data. Data Engineers are architects of these data platforms and give value to data analysis, business intelligence, and machine learning. In this course, you will learn to create and manage data infrastructures and build and deploy data pipelines to explore the various techniques to optimize large volumes of data and algorithms. You will also get to work with large and multi databases and learn how to create a Python data pipeline from scratch.
Find out how tree data structures speed up the processing of data analysis. As you move on, you will also learn to work with complex data that are collected from multiple sources to build data processing systems. This course will give you an understanding of the skills involved in descriptive and inferential analysis and how data processing is optimized using various tools like NumPy. Also, learn to analyze data in Python and take a dive into object-oriented programming (OOP). Understand data warehouse and data manipulation and learn how to use Big Query ML to build different kinds of ML models. Join the Data Engineering course to get a hands-on introduction to developing and building data pipelines. Also-
- Master Python for data wrangling, EDA, and visualization using Pandas, Seaborn, and Plotly build and query relational databases with advanced SQL and PostgreSQL
- Perform data cleaning, sampling, and transformation for real-world data scenarios
- Design and implement ETL/ELT workflows using SQL and NoSQL for cloud and on-premises
- Deploy big data pipelines using Kafka, Hadoop, Spark, and other distributed frameworks
- Work with data lakes, warehouses, and lakehouses across AWS, Azure, and GCP
- Gain exposure to cutting-edge tools like Databricks, Snowflake, Neo4j, and GenAI datastore technologies
Data Engineering Course Modules
These modules are going to take you through the essential skills required to become a successful data engineer. You will learn how to gather, extract, transform, and then deploy data pipelines in the cloud. Using big data tools and real-time multiple databases you will gain expertise in skills of refining, and exchanging data. These modules are crafted keeping in mind the current industry trends and market requirements.
- Prompt Engineering & Context Engineering
- Generative AI Foundations
- Agentic AI, MCP, A2A
- Beyond Vibe Coding – Vibe Coding Bootcamp
- AI Systems Performance Engineering
- CRISP-ML(Q)
- EDA using AutoEDA with Vibe Coding
- Data Preprocessing using Auto Data Prep Libraries
- Best Practices with Coding Assistants
- Data Analytics & Big Data using PySpark
- Agentic Coding for Python Workflows
- Parallel Processing & Compute Optimization
- Text-to-SQL & AI SQL Copilots (60 mins)
- IDE Integration & Query Acceleration
- Open Source, Security & Governance (60 mins)
- Big Data Processing
- Azure Data Engineering
- AWS & Snowflake
- GCP, Orchestration & AI/ML Data Engineering
10 Real-World Business Use Cases
GenAI assistants and models
- ChatGPT
- Claude
- Gemini
- Llama
- Perplexity
AI-assisted and vibe coding
- GitHub Copilot
- Cursor
- Claude Code
- Replit
Agentic AI frameworks
- LangChain
- Hugging Face
- Ollama
Zero-code AI automation
- n8n
- Zapier
- Make
Deploy and MLOps
- MLflow
- Streamlit
- Docker
- Databricks
- AWS
- Google Cloud
Trends in Data Engineering Certification
A Data Engineer deals with delivering data analytics across various systems using data modeling, data storage, data transforming, and data maintenance. With high demand in the data engineering services market and with growth estimates from 18.3% to an unbelievable 31.5% p.a., consulting firms like Accenture and other tech companies like Cognizant are in dire need of data engineers who can capture big data, to govern, analyze, tag, and utilize. AI will take care of repetitive tasks in the field of quality assurance that will reduce the time consumed while performing these tasks.
With increasing development in software, data engineers will also be seen leveraging HTTP/3 in the layer of data collection for communicating across the web. For smooth exchange of data and distributed storage, the use of blockchain technology will also be seen in action along with the use of the AWS Lambda function by data engineers to process and execute data pipelines.
"The global big data and data engineering market is projected to exceed $115 billion USD by 2028, with a CAGR of over 15% — highlighting an urgent need for skilled professionals across cloud, data lakes, and real-time analytics.” — Source: Fortune Business Insights, 2024
"More than 70% of companies now cite data engineering as their top hiring priority within analytics teams."— Gartner Data & Analytics Trends Report, 2023
How we prepare you
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Additional assignments of over 80+ hours
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Live Free Webinars
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Resume and LinkedIn Review Sessions
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Lifetime LMS Access
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100% Practical Oriented Course
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Complimentary Courses
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Hands-on experience in a live project
Call us Today!
+60 19-383 1378Data Engineering Course Panel of Coaches
Bharani Kumar Depuru
- Professional Experience: Over 18+ years in data analytics, digital transformation, and Industrial Revolution 4.0.
- Expertise: Specializes in data analytics and digital transformation.
- Corporate Clients: Worked with Deloitte, HPE, Amazon, Tech Mahindra, Cummins, Accenture, and IBM.
- Certifications: PMI-ACP, PMI-RMP, Lean Six Sigma Master Black Belt, Tableau Certified Associate, Certified Scrum Practitioner.
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Samson Swaroop Paturi
- Professional Experience: Over 17+ years in machine learning, AI, and big data/data lake systems.
- Expertise: Specializes in machine learning, AI, and big data.
- Experience: Worked with Capgemini, Florida Power & Light Company, ComTec Information Systems, and IBM.
- Certifications: Certified Scrum Product Owner (CSPO), Six Sigma Green Belt, ITIL Foundation Level, IBM logo Advisory Product Services Professional.
Aman
- Professional Experience: Over 10 years of experience in Data Science and Analytics.
- Expertise: Specializes in Analytics, Business Intelligence (BI), Data Science, and Artificial Intelligence (AI).
- Solutions Experience: Senior Data Specialist at 360DigiTMG and AiSPRY.
- Certifications: Python, SQL, Power BI, Tableau.
Data Engineering Certificate
Win recognition for your skills with the Data Engineering Certification. Stand out in this emerging yet competitive field with our certification.
This programme carries international accreditation from the State University of New York (SUNY), USA, validating the curriculum against internationally recognised standards in data engineering education.
Alumni Speak
"Coming from a psychology background, I was looking for a Data Science certification that can add value to my degree. The 360DigiTMG program has such depth, comprehensiveness, and thoroughness in preparing students that also looks into the applied side of Data Science."
"I'm happy to inform you that after 4 months of enrolling in a Professional Diploma in Full Stack Data Science, I have been offered a position that looks into applied aspects of Data Science and psychology."
"360DigiTMG’s Full Stack Data Science programme equips its graduates with the latest skillset and technology in becoming an industry-ready Data Scientist. Thanks to this programme, I have made a successful transition from a non-IT background into a career in Data Science and Analytics. For those who are still considering, be bold and take the first step into a domain that is filled with growth and opportunities.”
"360DigiTMG is such a great place to enhance IR 4.0 related skills. The best instructor, online study platform with keen attention to all the details. As a non-IT background student, I am happy to have a helpful team to assist me through the course until I have completed it.”
"I think the Full Stack Data Science Course overall was great. It helped me formalize and think more deeply about ways to tackle the projects from a Data Science perspective. Also, I was remarkably impressed with the instructors, specifically their ability to make complicated concepts seem very simple."
"The instructors from 360DigiTMG were great and it showed how they engaged with all the students even in a virtual setting. Additionally, all of them are willing to help students even if they are falling behind. Overall, a great class with great instructors. I will recommend this to upcoming deal professionals going forward.”
Our Alumni Work At
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FAQs for Data Engineering Certification Training
A data engineer designs, builds, and maintains the data pipelines and infrastructure that organisations use to collect, store, and process data at scale. In Malaysia, demand for data engineers has grown significantly as organisations invest in cloud platforms and real-time analytics capabilities.
The programme covers Apache Spark, Kafka Streaming, Azure Data Platform, Azure Pipelines, AWS Data Engineering, Snowflake, GCP, and Apache Airflow — the most in-demand data engineering platforms in the Malaysian and ASEAN job market.
Is this data engineering course HRD Corp claimable, we support the documentation?
Yes — this programme is HRD Corp claimable, we support the documentation (Registration No. 10001313781). Employers registered with HRD Corp can submit claims to cover course fees, making the effective cost to the learner zero.
A data engineer builds the systems and pipelines that move and store data. A data scientist uses that data to build predictive models and generate insights. Both roles work together — data engineers provide the infrastructure; data scientists provide the analysis.
Yes — basic Python familiarity is required. The programme uses AI-assisted tools to accelerate coding, but a technical background and basic database understanding are expected.
The Data Engineering course aims to provide aspirants with an in-depth understanding of all the essential tools and skills used by Data Engineers. The course provides hands-on learning of leading as Python, SQL, Spark, Kafka, and many more.
The training will be conducted in hybrid mode i.e., through the live instructor-led virtual sessions. The timings for both the sessions will be the same.
After the successful completion of 80% of your assignments, you are assigned to a live project where you will work with a group of students to bring the project to closure. After that, you will make a project presentation.
After the successful completion of the program, you will be awarded the Data Engineering certificate, powered by IBM.
This course is designed for students as well as working professionals. The basic requirement to undertake this course includes a degree in engineering, computer applications, or mathematics.
No, there are no extra charges for the certification. The cost is included in the package.
If you miss out on a session, there’s no need to worry. You can easily access the recorded session from the data engineer online course platform, available through our online Learning Management System (LMS). This ensures you can catch up with the missed material at your own pace.
Becoming a data engineer in 3 months is challenging but possible with focus and dedication. Start by learning the fundamentals of data engineering—essential programming languages like Python and SQL, as well as data storage technologies like Hadoop and Spark. By dedicating time to coursework, practical projects, and continuous learning, you can fast-track your journey into data engineering.
When considering learning data engineering, 360DigiTMG offers comprehensive courses designed to equip individuals with the necessary skills and knowledge. Their programs typically cover key concepts in data engineering, programming languages such as Python and SQL, as well as relevant technologies like Hadoop, Spark, and data pipelines. Depending on the course structure and individual effort, completing such a program could significantly accelerate the learning process.
Jobs in Data Engineering In Malaysia
The demand for skilled Data Engineers is growing rapidly paving way for many job opportunities which involve collaboration with Data Scientists, Database Administrators, and Data Architects.
Salary for Data Engineers
Data Engineers are among the highest-paid professionals and perform various roles to support business applications by maintaining data infrastructure. The average salary of a Data Engineer with 1-5 years of experience can range from 5lacs to 8lacs per annum.
Projects in the field of Data Engineering
The various big data projects that data engineers can work on include processing unstructured data using Spark, analyzing datasets with songs to predict song preferences, or analyze an airline dataset using big data tools like Hadoop and Hive.
Role of Open Source Tools in Data Engineering
The open-source tools help to transform and extract data which is then used to implement pipeline models. The various tools of data engineering include Hadoop, SQL, and NoSQL, Apache Spark, Python, etc.
Modes Of Training For Data Engineering
The course in Data Engineering is designed to suit the needs of students as well as working professionals. We provide our students the option of interactive live online learning which is supported by theory and practical methodology.
Industry Applications of Data Engineering
Data Engineers can work in sectors like banking, marketing, education, healthcare, manufacturing, media, etc., and can work as a generalist data engineer, pipeline-centric data engineer, and database-centric data engineer depending upon the job requirement.
Companies That Trust Us
360DigiTMG offers customised corporate training programmes that suit the industry-specific needs of each company. Engage with us to design continuous learning programmes and skill development roadmaps for your employees. Together, let’s create a future-ready workforce that will enhance the competitiveness of your business.
Student Voices
Sana Ahsan
5 years ago
Suriyaa Kumar
5 years agoI attended the Certification in Data Science program by 360DigiTMG. The course was amazing. I had a great learning & networking experience. Also, trainers are highly experienced and knowledgeable in the field of Data Science. I will recommend this course to anyone who wants to become a Data Scientist.
Asyraaf Afandi
5 years agoI joined the Data Science Certification Program which is a great place to learn if you want to start your career in the Data Science industry. The trainers are very knowledgeable and will try to explain the topics until you truly understand it. I would definitely recommend others to join it.
Iqmal Harris
5 years agoThe courses are taught by seasoned industry experts who know how to train absolute beginners and established professionals alike. Glad to have trained under 360DigiTMG.
Zarif Iqram
4 years agoI worked on a Survival Analysis project, which gave me good exposure and boosted my skill set in Business Intelligence with Power BI. Good to have it more and be involved in the real-time projects.
360DigiTMG - 360DigiTMG - Data Science, IR 4.0, AI, Machine Learning Training in Malaysia
Level 16, 1 Sentral, Jalan Stesen Sentral 5, Kuala Lumpur Sentral, 50740 Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia
Data Engineering Certification Course Training in Other Locations - Data Engineering Course in Malaysia, Data Engineering in Malaysia, Data Engineering Courses, Data Engineer Course, Data Engineer Malaysia, Data Engineering Course in Bangalore, Data Engineering Course in Hyderabad, Data Engineer Certification, Data Engineering, In Malaysia, the Data Engineering Course acts as the gateway to uncovering valuable insights from extensive datasets. It serves as the communication channel through which data conveys essential information to address contemporary business requirements. Pursuing certification guarantees mastery in crafting, executing, and refining data solutions to meet evolving demands..
What stood out most was the programme's practical and structured approach to AI adoption. The industry-specific examples, combined with clear frameworks for evaluating feasibility and designing solutions, made the learning highly relevant to our business.
What stood out most was the trainer's simple way of explaining Data Science and GenAI, and showing us different AI tools that I had not used before. It made me realise how useful these tools can be in our daily work.
