Data Engineer
April 10, 2026 2026-04-27 18:20Data Engineer
Data Engineer
Build specialized data engineering skills in pipeline design, ETL and ELT workflows, data warehousing and lakehouse concepts, distributed processing, data quality, governance support, and production-style platform delivery.
- Credential: Diploma
- Clock Hours: 90
- Build specialized preparation in pipelines, ETL and ELT engineering, warehousing, and distributed processing.
- Progress through a structured 7-module diploma with guided labs and a production-style capstone project.
- Prepare for roles in data engineering, platform delivery, and scalable data infrastructure support.
ICCT in Numbers
Since 2019, weβve helped students build practical career-ready skills through hands-on, online-led programs.
2019
Operating since
1000+
Student success stories
35 yrs
Instructor experience
97%
Learner satisfaction rate
Why this program & who itβs for
This diploma is designed for students ready to move beyond domain-level preparation and build specialized data engineering competencies in platform workflows, pipeline delivery, data movement, and scalable data operations.
Build focused engineering competencies
Develop specialized preparation in pipeline design, orchestration, ETL and ELT workflows, data warehousing and lakehouse concepts, distributed processing, governance support, observability practices, and AI-assisted engineering productivity.
What youβll be able to do
Design and support data pipelines, implement structured data movement and transformation workflows, apply warehouse and lakehouse concepts, support data quality and observability practices, and contribute to scalable data platform delivery.
Delivered for applied learning
Instruction is delivered through distance/hybrid education in mostly an online format using instructor-supported lectures, demonstrations, guided practice, lab assignments, and applied exercises.
Recommended preparation
Successful completion of Data Analytics, AI and Business Intelligence Domain is recommended before entering this diploma program.
Program Structure
The program is organized as a focused clock-hour diploma consisting of seven required modules. Instruction progresses through pipeline design, ETL and ELT engineering, data warehousing and lakehouse architecture, distributed processing, governance and observability practices, and AI-assisted engineering productivity, culminating in a production-style capstone project.
DE-301 β Data Pipeline Design and Orchestration
15 hrs- Batch and streaming concepts
- Pipeline workflows
- Job dependencies
- Orchestration patterns
DE-302 β ETL and ELT Engineering
15 hrs- Data ingestion
- Transformation
- Load strategies
- Pipeline reliability
- Schema handling
DE-303 β Data Warehousing and Lakehouse Architectures
15 hrs- Warehouse design
- Lakehouse concepts
- Storage layers
- Partitioning and modeling
DE-304 β Distributed Data Processing
10 hrs- Scalable processing concepts
- Parallel workflows
- Distributed compute principles
DE-305 β Data Quality, Governance, and Observability
10 hrs- Validation rules
- Lineage concepts
- Monitoring
- Governance support
- Reliability metrics
DE-306 β AI for Data Engineering and Pipeline Automation
10 hrs- AI-assisted code generation
- Pipeline design aids
- Automation tools
- Documentation support
DE-307 β Capstone Project: Production-Style Data Platform Build
15 hrs- Source-to-target pipeline
- Warehouse integration
- Monitoring
- Delivery documentation
See the full career pathway structure
Explore all available program routes, specializations, and next-step options.
βDiploma tuition & fees
$5,000
Data Engineer Β· 90 clock hours
- Focused clock-hour diploma consisting of seven required modules
- Instructor-supported lectures, demonstrations, guided practice, lab assignments, and applied exercises
- Includes assigned labs and a production-style capstone project for specialized data engineering preparation