Data Engineering Professional
Build and maintain the infrastructure that powers modern data analytics. Master database systems, ETL processes, big data technologies, and cloud-based data architectures.
High-Demand Skills
The Data Engineering Lifecycle
Learn to build efficient data pipelines that transform raw data into valuable business assets
Data Sources
Databases, APIs, streams, files
Extraction
Accessing and retrieving data
Transformation
Cleaning, enriching, processing
Loading
Target storage and schema
Analytics
Reporting and insights
Master the Data Engineering Stack
Data engineers are the architects who design, build, and maintain the infrastructure that enables data-driven decision making. Our comprehensive course equips you with the technical expertise to develop robust data pipelines, storage solutions, and processing systems.
You'll gain hands-on experience with both traditional database systems and modern big data technologies, learning to bridge the gap between raw data and analytics-ready information.
Core Competencies You'll Develop
Course Details
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Duration
14 weeks, 3 sessions per week (2 weekday evenings + Saturday morning)
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Prerequisites
Basic programming knowledge. Familiarity with databases and SQL is helpful but not required.
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Technologies Covered
SQL, Python, Apache Spark, AWS, Docker, Kafka, Airflow, Hadoop ecosystem
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Career Paths
Data Engineer, ETL Developer, Cloud Data Architect, Big Data Engineer, Data Infrastructure Specialist
Technologies You'll Master
Gain hands-on experience with the most in-demand data engineering tools and platforms
SQL
Advanced query optimization and database design
Python
Data processing and pipeline development
Spark
Big data processing and analytics
Airflow
Workflow scheduling and orchestration
Kafka
Real-time data streaming
AWS
Cloud-based data infrastructure
Docker
Containerization for data services
Hadoop
Distributed storage and processing
Course Curriculum
A comprehensive learning journey from database fundamentals to advanced data pipeline engineering
Foundations of Data Engineering
Introduction to the data engineering landscape, roles, and responsibilities. Understand the data lifecycle, key components of data infrastructure, and the relationship between data engineering and other data disciplines.
Topics Covered:
- Data engineering ecosystem
- Data pipeline architecture
- ETL vs ELT processes
- Data engineering tools overview
Relational Database Design & SQL
Master advanced SQL techniques and database design principles. Learn to create efficient schemas, optimize queries, and manage database performance for data engineering workloads.
Topics Covered:
- Database normalization
- Advanced SQL joins and subqueries
- Query optimization techniques
- Indexing strategies
Project: Design and implement a normalized database for a complex business scenario
Python for Data Engineering
Develop Python programming skills specifically for data engineering tasks. Learn to use libraries such as Pandas, SQLAlchemy, and Requests for data manipulation, database interactions, and API integrations.
Topics Covered:
- Data manipulation with Pandas
- SQLAlchemy for database access
- API integration and web scraping
- Data transformation scripts
Project: Develop a Python ETL script that extracts data from an API, transforms it, and loads it into a database
ETL Process Development
Learn the principles and practices of building efficient Extract, Transform, Load (ETL) processes. Design data pipelines that handle data extraction from various sources, complex transformations, and loading into target systems.
Topics Covered:
- Data extraction techniques
- Data transformation patterns
- Data loading strategies
- ETL error handling and recovery
Project: Design and implement a complete ETL pipeline for a business analytics scenario
Meet Your Instructors
Learn from experienced data engineering professionals with real-world industry expertise
Stanislav Chorvatski
Lead Data Engineering Instructor
Former AWS cloud architect with expertise in data pipeline construction. Has trained over 400 engineers in big data technologies and led major data infrastructure projects.
Expertise & Experience
- PhD in Computer Science from Zagreb Institute
- 10+ years in cloud architecture and data engineering
- Built data infrastructure for major financial institutions
- AWS certified Solutions Architect and Big Data Specialist
Aleksandra Moldovanova
Big Data & Streaming Specialist
Data engineering expert specializing in big data technologies and streaming systems. Previously worked as a Data Architect at Netflix and Databricks, leading large-scale data initiatives.
Expertise & Experience
- MSc in Data Engineering from Bucharest Tech
- 8+ years of experience with Spark, Kafka, and Hadoop
- Built real-time recommendation systems at scale
- Contributor to Apache Kafka and Apache Beam projects
Career Outcomes
Where our data engineering graduates find success in the job market
96%
Job Placement Rate
Data engineering is one of the most in-demand tech specializations in Cyprus and globally.
€15,000+
Average Salary Increase
Our alumni report substantial salary improvements after completing the program.
50+
Hiring Partners
Leading tech companies and enterprises actively recruit our graduates.
Top Job Titles Of Our Graduates
Data Engineer
Average Salary: €65,000 - €85,000
45% of graduates
Cloud Data Architect
Average Salary: €70,000 - €95,000
22% of graduates
Big Data Engineer
Average Salary: €60,000 - €80,000
15% of graduates
Data Infrastructure Specialist
Average Salary: €60,000 - €80,000
12% of graduates
Career Support Services
Your success extends beyond the classroom. Our dedicated career services team provides comprehensive support to help you land your dream data role:
CV & LinkedIn Optimization
Professional guidance to showcase your technical skills effectively
Technical Interview Prep
Mock interviews and coding challenges specific to data engineering roles
Industry Networking
Exclusive events with hiring partners and industry professionals
Frequently Asked Questions
What technical background do I need for this course?
While some programming knowledge is helpful, our course is designed to accommodate various backgrounds. We recommend basic familiarity with programming concepts and database fundamentals. If you're comfortable with basic coding and SQL queries, you'll be well-prepared. We provide pre-course preparatory materials to ensure everyone starts with the necessary foundation.
How does this course differ from the Data Analysis course?
The Data Engineering course focuses on building and maintaining the infrastructure that enables data analysis. While data analysts work with data to derive insights, data engineers create the systems that collect, store, and process data at scale. This course covers specialized topics like database design, ETL pipelines, big data processing, and cloud infrastructure that are not covered in depth in our analysis course. Think of data engineers as the architects who build the foundation that analysts work upon.
What projects will I complete during the course?
Throughout the course, you'll work on numerous hands-on projects that simulate real-world data engineering challenges. These include designing database schemas, building ETL pipelines, creating data warehousing solutions, implementing real-time streaming systems, and deploying cloud-based data architectures. Your capstone project will involve building a complete end-to-end data engineering solution that addresses a real business need, which becomes a key portfolio piece for your job search.
What kind of computer or setup do I need?
You'll need a laptop with at least 8GB RAM (16GB recommended) and a modern operating system (Windows 10+, macOS 10.14+, or Linux). While most practical work will be done on cloud platforms with provided access, having a reasonably powerful system ensures smooth local development. We'll provide detailed setup instructions before the course begins. All software used in the course is free or open-source, though some cloud services may require creating accounts (free tiers are available for educational purposes).
Are there any certifications included?
The course includes preparation materials for key industry certifications such as AWS Certified Data Analytics, Google Cloud Professional Data Engineer, and Databricks Certified Associate Developer. While the certification exams themselves are not included in the course fee, we provide resources, practice exams, and guidance to help you prepare for these certifications after completing our program. Our course completion certificate is also well-recognized by employers in Cyprus and internationally.
What payment options are available?
We offer several payment options including upfront payment with a 7% discount, monthly installment plans (3, 6, or 12 months) at no additional cost, and employer sponsorship arrangements. We also partner with select financial institutions to offer education loans with favorable terms. For eligible students, we offer a limited number of partial scholarships based on merit and need. Please contact our admissions team for detailed information about our current payment plans and scholarship opportunities.
Data Engineering Training in Cyprus
As organizations in Cyprus increasingly embrace digital transformation, the demand for skilled data engineering professionals has grown exponentially. Data engineering represents the critical infrastructure layer that enables modern data-driven decision making across industries—from financial services and tourism to emerging technology sectors that form the backbone of Cyprus's evolving economy.
The particular complexity of data engineering in the Cypriot context stems from the need to integrate with both European and Middle Eastern data systems, navigate EU regulatory frameworks like GDPR, and address the unique challenges of building robust data infrastructure in a regional business hub. These factors create substantial opportunities for professionals with specialized data engineering expertise.
What distinguishes excellence in data engineering education is the balance between theoretical foundation and practical implementation. While understanding concepts like database design, ETL processes, and distributed systems is essential, true proficiency comes from hands-on experience building and troubleshooting real-world data pipelines that address business challenges specific to regional industries.
The financial services sector, which forms a cornerstone of the Cypriot economy, demonstrates particularly strong demand for data engineering capabilities. From building data warehouses that enable regulatory compliance to creating streaming architectures for real-time analytics, banks and financial institutions require sophisticated data infrastructure that balances security, performance, and accessibility.
Similarly, the tourism industry, a traditional economic pillar of Cyprus, has increasingly recognized the competitive advantage offered by robust data architecture. The ability to capture, process, and analyze visitor data at scale enables personalized marketing, dynamic pricing strategies, and operational optimization that directly impacts profitability.
For professionals considering career development in this field, data engineering offers particularly compelling returns on educational investment. The specialized nature of these skills, combined with growing demand and limited supply of qualified engineers, has created a premium salary market that typically exceeds other technical roles by 15-25% in the Cypriot job market.
Beyond immediate employment prospects, data engineering skills provide exceptional career durability. As organizations continue to generate exponentially increasing volumes of data, the need for professionals who can design and maintain the infrastructure to harness this information will only grow—creating a foundation for long-term career progression in Cyprus's increasingly knowledge-based economy.
When evaluating data engineering educational options, prospective students should prioritize programs that offer hands-on experience with the full spectrum of modern data technologies—from traditional databases to cloud platforms, big data systems, and streaming architectures. This comprehensive skill set ensures graduates can address the diverse and evolving data needs of Cypriot employers across sectors.
Ready to Become a Data Engineer?
Our next cohort starts November 12, 2025. Spaces are limited to ensure personalized attention and high-quality learning experience.
Application Process
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1
Complete the Application
Fill out our online form (takes about 10 minutes)
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2
Technical Assessment
Complete a basic assessment to ensure course fit
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3
Admission Interview
Brief discussion about your background and goals
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4
Enrollment & Preparation
Secure your spot and begin pre-course materials
Questions? Contact us for more information about the program.