Certified Data Engineer Professional
A 120-hour data-engineering certification — building the pipelines and platforms behind analytics and ML, from SQL and Python to Airflow, BigQuery, Beam and Spark. You build the batch and streaming pipelines that feed analytics and machine learning at scale.
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Course Info
- Type
- Certification
- Subject
- Individual & Professional Certification
- Duration
- 120 hours
- Course code
- CDEP
- Prerequisites
- Comfort with basic computing; foundational programs available if needed.
Delivery
- Live-virtual — Instructor-led online cohorts.
- On-site — In-person at your premises or ours.
- Self-paced — Learn on your own schedule.
Tools
- Python
- SQL
- Pandas
- MongoDB
- Airflow
- BigQuery
- ETL
- PubSub
- Beam
- Spark
What you'll learn
A 120-hour data-engineering certification — building the pipelines and platforms behind analytics and ML, from SQL and Python to Airflow, BigQuery, Beam and Spark. You build the batch and streaming pipelines that feed analytics and machine learning at scale.
You move from Python, SQL and Pandas to databases, ETL, orchestration and cloud warehousing, then to streaming and big-data processing. The capstone builds an end-to-end data platform.
- Analysts and developers moving into data engineering.
- Engineers building ETL and streaming data platforms.
- Model and query data with SQL, Python and Pandas.
- Design and build batch ETL pipelines.
- Orchestrate workflows with Airflow.
- Build streaming pipelines with Pub/Sub and Beam.
- Process big data with Spark on the cloud.
- Hands-on labs throughout the program (70% project-based).
- A capstone project demonstrating end-to-end skills.
- Design and operate batch and streaming data pipelines.
- Build cloud data platforms with BigQuery, Airflow and Spark.
Globally accredited certificate issued by Epsilon AI Learning — USA, with a unique Certificate ID and EPSILON ID. Awarded on 80% attendance, 80% final exam, and a capstone project.
Program Curriculum
- Python and SQL for pipelines
- Data wrangling with Pandas
- Relational databases and MongoDB
- Extract, transform, load patterns
- Data quality and validation
- Incremental and idempotent loads
- DAGs, scheduling and dependencies
- Retries, backfills and monitoring
- Parameterized, reusable workflows
- Modeling data in BigQuery
- Partitioning, clustering and cost control
- Serving analytics-ready datasets
- Real-time pipelines with Pub/Sub & Beam
- Distributed processing with Spark
- Batch vs. streaming trade-offs
- Designing an end-to-end architecture
- Building batch and streaming flows
- Delivering a production-grade pipeline
Frequently asked questions
What background do I need?
Comfort with basic programming helps; the program covers Python, SQL and Pandas from a practical footing before moving to pipelines and cloud tooling.
Does it cover both batch and streaming data?
Yes — you build batch ETL with Airflow and BigQuery, then real-time streaming pipelines with Pub/Sub, Beam and Spark.
How is it different from the Big Data program?
Data engineering focuses on building pipelines and cloud data platforms; the Big Data program focuses on the Hadoop/Spark ecosystem and processing data at massive scale.
How much does the program cost?
Pricing depends on the format you choose — online, onsite, or a corporate cohort — and any current offers. Fill in the registration form on this page and an Epsilon team member will contact you with the exact price and the options that fit you.
When does the next cohort start?
New cohorts open regularly across online and onsite formats. Fill in the registration form and our team will contact you with the next available start dates that fit your schedule.
Is the program online or onsite, and in which language?
Both — Epsilon runs live, instructor-led sessions online and onsite, plus dedicated corporate cohorts. Programs are delivered in English and Arabic, with bilingual materials and instructor support. Tell us your preference in the registration form.
What certificate will I receive?
A globally accredited certificate from Epsilon AI Learning — USA, carrying a unique Certificate ID and Epsilon ID. It is awarded on 80% attendance, an 80% final exam, and a completed capstone project, and it is verifiable online.
Continue your pathway
This program is part of the Epsilon certification framework. Explore the full seven-level pathway and top-up programs to build on what you learn here.
Data Engineer
- Certified Data Engineer Professional
Led by Epsilon's expert instructors
Every program is delivered by practitioners who ship AI and analytics in industry — the same team across all Epsilon programs.
Where our graduates work
A sample of the employers hiring Epsilon Learning graduates across the region and beyond.
Earning your accredited certificate
To receive the accredited certificate you must pass both the placement test and the practical test with at least 80%, and complete the program fees.
Register — Certified Data Engineer Professional
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