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MSc Data Engineering

The MSc in Data Engineering is a 12-month postgraduate program designed to develop skilled professionals capable of designing, building, and managing large-scale data systems. Through hands-on projects, case studies, and a master’s thesis, students gain practical experience in creating scalable data solutions, integrating AI, and addressing real-world data challenges. Graduates emerge ready for leadership roles as Data Engineers, Cloud Data Specialists, or Big Data Analysts in data-driven organisations.

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  • Duration

12 Months

  • Modules

12 Modules

  • Credits

60 ECTS

  • Format

Blended Learning

  • Projects

2 Projects

  • Assessment

Exams & Vivas

Globally Recognized & Accredited:

1

Ai & Data School

60

Credits for Masters Program

95

Career Transition Rate

100

Online Flexibility

  • Industry-Standard Technology Stack

Tools & Technologies That Power Success

Gain hands-on experience with the core tools and platforms that power modern data engineering. The MSc in Data Engineering equips students to build scalable data pipelines, deploy cloud-based solutions, and manage distributed data systems, preparing them to tackle complex real-world challenges.

  • Production-Ready Skills
  • Industry-Relevant Tools
  • Hands-On Learning

Python

Redis

Data Factory

Hadoo[

Apache Flink

Apache Spark

GCP

AWS Glue

Zookeeper

MongoDB

learn r project from airtics.org

R Project

No SQL Database

Join Airtics Education
  • Industry-Standard Technology Stack

Tools & Technologies That Power Success

Gain hands-on experience with the core tools and platforms that power modern data engineering. The MSc in Data Engineering equips students to build scalable data pipelines, deploy cloud-based solutions, and manage distributed data systems, preparing them to tackle complex real-world challenges.

  • Production-Ready Skills
  • Industry-Relevant Tools
  • Hands-On Learning

Python

Redis

Data Factory

Hadoop

Apache Flink

Apache Spark

GCP

AWS Glue

Zookeeper

Map Reduce

learn r project from airtics.org

R Project

No SQL Database

Join Airtics Education

Learn from France’s #1 Data Science School

Aivancity, currently ranked #1 in France for Artificial Intelligence and Data Science by Eduniversal 2025, has partnered with Airtics Education to deliver globally recognised programs. Combining Aivancity’s excellence in technology, business, and ethics with Airtics’ practical, industry-focused approach, the program covers data analysis, big data technologies, machine learning, data governance, and strategic use of data. Through hands-on projects, case studies, and a master’s thesis, students gain the skills and insight needed to handle complex datasets, design impactful data-driven solutions, and excel as strategic, ethical leaders in their careers.

Eligibility

Eligibility

This program is ideal for graduates, working professionals, or anyone aspiring to build a career in Data Science or Data Management. Applicants should have completed a 3 or 4-year bachelor’s degree in computer science, a related field, or have substantial experience in database management or object-oriented programming. A strong understanding or experience in statistics, a business-oriented mindset (including professional projects or internships), and interest in technology ethics or regulation are recommended. Candidates should be able to present an academic or professional project in any of these fields.​

Prerequisites

Applicants should possess a foundational understanding of mathematics, logical reasoning, and statistics. Familiarity with programming languages (such as Python, R, or SQL), as well as experience or education in database management or data analysis, will be helpful. Previous knowledge or experience in business, statistics, and technological ethics is preferred but not mandatory for admission.​

Course Modules

Unit 1
Big Data Management
Unit 2
Large Scale Data Services
Unit 3
Cloud Innovations
Unit 4
Big Data & Society
Unit 5
Project & Development Personnel
Foundations of Big Data Systems

 Gain a deep understanding of big data characteristics, distributed storage, and the architecture powering modern data platforms.

Cloud Deployment & Programming

 Master public, private, and hybrid cloud environments while building scalable applications using Scala.

Big Data in Practice

 Develop hands-on skills in Hadoop, Spark, and workflows for managing and transforming large data sets.

Learning Outcomes
Module Summary Duration: 4-6 weeks

By completing big data management, you will:

  • Critically evaluate big data design principles, distributed storage, and reliability trade-offs.

  • Demonstrate cloud deployment models and develop scalable data-intensive apps in Scala.

  • Execute data operations and workflows in Hadoop and Spark for large-scale analysis.

 

Cloud Service Platforms

 Explore major services like AWS, Azure, and GCP for data architecture and resource optimization.

Machine Learning for Data Engineering

 Integrate AI, machine learning, and deep learning into engineering workflows for scalable solutions.

Data Pipeline Development

Design ETL and ELT pipelines, leveraging modern tools for flexible, scalable data flows.

Learning Outcomes
Module Summary Duration: 4-6 weeks

By completing large scale data services modules, you will:

  • Critically deploy and optimize cloud-based data services.

  • Apply ML/DL algorithms for structured and unstructured data.

  • Build robust, efficient data pipelines for real-world projects.​
Project Lifecycle Management

Plan, manage, and adapt full-cycle data engineering projects from business case to delivery.

NoSQL Database Systems

Develop expertise in MongoDB, Redis, Zookeeper and apply NoSQL models for distributed, flexible data storage.

Data Governance & Compliance

 Learn frameworks, policies, and controls for organizational data quality and regulatory compliance.

Learning Outcomes
Module Summary Duration: 4-6 weeks

By completing cloud innovations modules, you will:

  • Execute and document full data project lifecycles and business-aligned solutions.

  • Critically evaluate NoSQL architectures for diverse data types.

  • Design and audit data governance strategies in real environments.​
Data Security Practices

Evaluate threats and design security strategies, including cryptographic and blockchain-based solutions.

Green and Sustainable Computing

Analyze energy consumption in data centers and implement sustainable, resource-efficient engineering.

Ethical Data Practices

Address fundamental ethical issues—privacy, accountability, and fairness—in data-driven solutions and AI.

Learning Outcomes
Module Summary Duration: 4-6 weeks

By completing big data and society modules, you will:

  • Assess risks, threats, and apply security best practices for cloud data.

  • Design and implement energy-efficient, sustainable data solutions.

  • Create responsible, transparent systems that address data ethics.​
Capstone Master Thesis

Plan and deliver an independent project that synthesizes all program domains, solving a real data engineering challenge.

Industry Collaboration

Work directly with stakeholders or on advanced research to propose, implement, and evaluate robust data solutions.

Review & Presentation

Compile findings into a professional paper and presentation for technical/non-technical audiences.

Learning Outcomes
Module Summary Duration: 4-6 weeks

By completing big data and society modules, you will:

  • Analyze complex business problems and design scalable data solutions.

  • Evaluate performance and impact of engineering solutions.

  • Communicate technical decisions and outcomes confidently to varied stakeholders.​

Your Success Story Starts Here

Every image here tells a story of transformation, dedication, and success. Be the next to wear the cap and gown. Enroll today, and let your journey begin.

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What Our Students Say

Every student has a story—of ambition, of challenge, of growth. In their own words, they share how Airtics became a turning point in their learning journey and helped them move closer to their goals.

Pemsith Ravi

Thanks to the support of this prestigious institution – airtics. I was able to earn a master’s degree in data science. I had a fantastic educational experience there, and they possess a highly competent and knowledgeable lecturing panel. Anyone looking to make it major in the data science field should enrol in their course.
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Zeeshan Ali

Airtics offers a truly transformative learning experience. The course content is up-to-date, the mentors are incredibly supportive, and the flexibility of the online platform made it easy to balance with my work. Highly recommended for anyone looking to upskill!

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Aalaa Shbair

The experience at Airtics College has been tremendous for me. It has illuminated my path and opened the way for me to become a developer of solutions in my workplace. I cherish every moment of this online learning experience and the supportive community of instructors and peers.

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Muhammad Fatouh

Airtics offered a great platform that allowed me to take a meaningful step forward in data science while balancing my demanding job as a telecom engineer. If you have a busy schedule and struggle with work-life balance, I encourage you to find a flexible platform like Airtics to pursue your goals.

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Al Tayyab Bakhsh

Coming from a non-technical background in marketing, switching to data science was challenging. The faculty at Airtics was incredibly helpful, especially my mentor Miss Piyali, who guided me with patience every step of the way. Their mentorship gave me the confidence to succeed.

  • Verified Review

Dilnawaz Qureshi

Airtics provides an impressive curriculum for Python Full Stack development that is both well-structured and up-to-date. This comprehensive approach ensures we acquire a thorough understanding of the field and are well-prepared for real-world challenges.

  • Verified Review

Charuhaas Shenoy

Airtics offers a truly transformative learning experience. The course content is up-to-date, the mentors are incredibly supportive, and the flexibility of the online platform made it easy to balance with my work. Highly recommended for anyone looking to upskill!
  • Verified Review

Madonna Ghanem

The resources provided by Airtics for AI and ML students are top-notch. The institute has a well-equipped virtual lab with the latest software, allowing us to experiment with complex algorithms. The online library offers a wide range of reference materials and research papers.
  • Verified Review

Dhruv Narse

Airtics provides a conducive learning environment for data analytics students. They have experienced faculty, and provide access to the latest software and tools used in the industry. This ensures that we are well-prepared for our future careers in the field.

  • Verified Review

Learn from Industry Leaders & Experts

Learn from the best in the field. Our faculty combines academic brilliance with industry expertise, featuring PhD holders, senior data scientists, and AI researchers from top organizations.

Ms. PIYALI MONDAL - B&W
Ms. Piyali Mondal Head of Department
Ms. Priti Mondal - B&W
Ms. Priti Mondal Associate Faculty
Dr. Abdullah El Nokiti - B&W
Dr. Abdullah El-Nokiti Professor
Dr. Meraj Inamdar - B&W
Dr. Mohd Merajuddin Inamdar Professor
Dr. Madhavi Vaidya - B&W
Dr. Madhavi Vaidya Professor
Dr. Poonam Chaudhari - B&W
Dr. Poonam Chaudhari Professor
Dr. Anup Maurya - B&W
Dr. Anup Kumar Maurya Professor
Dr. Milan Joshi - B&W
Dr. Milan Amrutkumar Joshi Industry Expert
Dr. Mohamed Elhaw - B&W
Dr. Mohamed Elhaw Industry Expert
Dr. Pradeep Tiwari - B&W
Dr. Pradeep Tiwari Industry Expert
Global Student Community

Students from 60+ Countries Worldwide

Frequently Asked Questions

Find answers to common questions about our Advanced Program in Data Science. Learn about program details, requirements, and what to expect from this 6-month certification course.
Why should I join the MSc Data Engineering program?

This program develops future-ready engineers skilled in designing, building, and managing large-scale data systems. You’ll learn big data, cloud platforms, and advanced AI integration, preparing you to lead in data-driven roles across industries.​

Do I need a technical background to apply?

Applicants should hold a bachelor’s degree in computer science or a related field, plus some experience in database management or programming. The course is designed for both IT professionals and motivated graduates seeking to advance in tech.​

What is the difference between Data Engineering and Data Science?

Data Engineering focuses on infrastructure: constructing data pipelines, managing big data, and building scalable cloud solutions. Data Science applies analytical methods to gain insights—both are crucial in modern organizations.​

What technical skills will I learn?

You’ll master tools like Hadoop, Spark, Scala, AWS, and NoSQL databases. Training covers cloud services, machine learning, data security, project deployment, and sustainable computing practices.​

How will the program prepare me for real-world roles?

Study blends theory with hands-on projects, cloud certifications, and a master’s thesis aligned to industry challenges. Graduates move into roles such as Data Engineer, Cloud Architect, or AI Solution Designer.​

Is ethical and sustainable computing addressed?

Yes. Modules teach data ethics, privacy, and legal compliance, along with green computing—reflecting the latest industry standards for responsible data innovation.​

Still have questions?

If you’d like more details about the MSc Data Engineering program—its curriculum, eligibility, or learning format—our team is ready to assist. Reach out to explore how this globally recognized program can help you advance your career in Data Engineering.

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