Data Science, AI, and Advanced Analytics Greece

Data Engineering and Workflow Automation Training Course

Data engineering is the practice of designing and building systems for collecting, storing, and analyzing data at scale. It involves creating robust pipelines that transform raw data into actionable insights. In a landscape where data volume and variety are accelerating, do you know if your current data infrastructure can handle the pressure of real-time analytical demands? Modern organizations are moving away from fragile, manual scripts toward automated, self-healing workflows using tools like Apache Airflow and dbt. Failure to modernize these pipelines leads to data silos, high latency, and decision-making based on stale information.

This course serves as the bridge from fragmented data tasks to high-performance automated systems. Can you demonstrate the reliability of your data to executive stakeholders when pipeline failures occur? This training is designed for Data Engineers, Analytics Engineers, and BI Developers who need to implement production-grade ETL and ELT processes. You will build tangible work products including automated Directed Acyclic Graphs (DAGs), optimized SQL models, and data quality dashboards. By the end of this program, you will transition from a reactive troubleshooter to a proactive architect of scalable data ecosystems.

Duration
10 Days
Duration
Certificate
Certificate
Included
Delivery
Instructor-Led
Delivery
Level
Foundation To Intermediate
Level
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Training Options

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Live Online Training

Join from anywhere with interactive virtual sessions

Starts
Ends
Mon - Fri (10 Days)
USD 1,700
Starts
Ends
Mon - Fri (10 Days)
USD 1,700
Starts
Ends
Weekend (8 Wks)
USD 1,700
Starts
Ends
Mon - Fri (10 Days)
USD 1,700
Starts
Ends
Weekend (8 Wks)
USD 1,700
Starts
Ends
Mon - Fri (10 Days)
USD 1,700
Starts
Ends
Mon - Fri (10 Days)
USD 1,700

Classroom Training

In-person sessions at premier locations

Nairobi Kenya
Mon - Fri
10 Days
USD 3,360
Kigali Rwanda
Mon - Fri
10 Days
USD 3,990
Dubai United Arab Emirates (UAE)
Mon - Fri
10 Days
USD 8,610
Zanzibar Tanzania
Mon - Fri
10 Days
USD 5,040
Customized Content
Team Training
Flexible Dates

In-person training at our premier venues — pick a city and date that works for you.

Location Duration Fee Language
Nairobi, Kenya Mon - Fri (10 Days) USD 3,360 English See dates & reserve →
Kigali, Rwanda Mon - Fri (10 Days) USD 3,990 English See dates & reserve →
Dubai, United Arab Emirates (UAE) Mon - Fri (10 Days) USD 8,610 English See dates & reserve →
Zanzibar, Tanzania Mon - Fri (10 Days) USD 5,040 English See dates & reserve →
Abuja, Nigeria Mon - Fri (10 Days) USD 5,880 English See dates & reserve →
Addis Ababa, Ethiopia Mon - Fri (10 Days) USD 4,900 English See dates & reserve →
Mombasa, Kenya Mon - Fri (10 Days) USD 3,570 English See dates & reserve →
Cape Town, South Africa Mon - Fri (10 Days) USD 8,190 English See dates & reserve →
Johannesburg, South Africa Mon - Fri (10 Days) USD 7,350 English See dates & reserve →
Kampala, Uganda Mon - Fri (10 Days) USD 3,990 English See dates & reserve →
Pretoria, South Africa Mon - Fri (10 Days) USD 6,930 English See dates & reserve →
Lagos, Nigeria Mon - Fri (10 Days) USD 5,250 English See dates & reserve →
Arusha, Tanzania Mon - Fri (10 Days) USD 4,200 English See dates & reserve →
Dar es Salaam, Tanzania Mon - Fri (10 Days) USD 3,990 English See dates & reserve →
Naivasha, Kenya Mon - Fri (10 Days) USD 3,570 English See dates & reserve →
Nakuru, Kenya Mon - Fri (10 Days) USD 3,360 English See dates & reserve →
Accra, Ghana Mon - Fri (10 Days) USD 8,295 English See dates & reserve →
Kisumu, Kenya Mon - Fri (10 Days) USD 3,360 English See dates & reserve →

Live, instructor-led sessions you can join from anywhere — pick the next start date below.

Code Start Date End Date Duration Fee
DSE-01 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →
DSE-01 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →
DSE-01 Weekend (8 Weeks) USD 1,700 Reserve my seat → Reserve team seats →
DSE-01 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →
DSE-01 Weekend (8 Weeks) USD 1,700 Reserve my seat → Reserve team seats →
DSE-01 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →
DSE-01 Mon - Fri (10 Days) USD 1,700 Reserve my seat → Reserve team seats →

Our instructor comes to your office — same curriculum and accredited certificate, with case studies built around the work your team actually does.

Team Training

Train your entire team together in a familiar environment for better collaboration

Fully Customized

Content tailored to your industry, tools, and specific business challenges

Cost Effective

Save on travel & accommodation costs when training multiple employees

Flexible Scheduling

Choose dates that work best for your team's availability and projects

How It Works
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2
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3
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About the Course

The core challenge in today's data-driven environment is not just collecting data, but ensuring its availability, integrity, and flow across the enterprise. Organizations require results they can prove through verifiable data lineage and automated governance. To achieve this, you need to master five critical capabilities: schema design for cloud warehouses, complex SQL transformation logic, Python-based pipeline scripting, workflow orchestration, and automated data quality testing. This course provides a structured system to turn scattered data sources into a unified, high-availability data lakehouse architecture using the Medallion Architecture pattern.

You will gain specific capabilities in building idempotent data pipelines, managing state in distributed systems, and implementing CI/CD for data infrastructure. You will practice hands-on deployment of Apache Airflow for orchestration and dbt for modular SQL modeling, while being introduced to the broader ecosystem of Apache Kafka for streaming and Kubernetes for containerized data tasks. This course is designed for professionals who must deliver high-uptime data services under the constraints of limited engineering resources and strict regulatory compliance requirements. Data Engineering and Workflow Automation Training is the definitive method for professionals to operationalize data at scale. It involves the integration of software engineering best practices into the data lifecycle. Professionals use it to reduce manual intervention, eliminate data downtime, and accelerate the time-to-insight for business intelligence teams.


Target Audience

This program is tailored for technical professionals responsible for the architecture, reliability, and automation of enterprise data assets.

This course is designed for:

  • Data Engineers responsible for building and maintaining scalable ETL/ELT pipelines
  • Analytics Engineering Leads overseeing modular SQL modeling and data transformation logic
  • ETL Developers transitioning from legacy on-premise tools to cloud-native automation
  • BI Architects designing the integration layer between data warehouses and visualization tools
  • Data Warehouse Administrators optimizing performance for Snowflake, BigQuery, or Redshift
  • Cloud Infrastructure Engineers supporting data platform deployments on AWS, Azure, or GCP
  • Data Quality Analysts implementing automated testing frameworks and observability dashboards
  • Platform Engineers managing containerized data workloads using Docker and Kubernetes
  • Machine Learning Engineers building automated feature engineering pipelines for production models
  • Software Developers moving into data-centric roles requiring workflow orchestration expertise

Course Objectives

This course equips you to design, execute, and report data engineering initiatives that ensure high availability, regulatory compliance, and strategic scalability.

By the end of this course, you'll be able to:

  • Construct scalable data architectures using the Medallion Architecture and Data Lakehouse patterns
  • Apply advanced SQL window functions and CTEs to solve complex data transformation challenges
  • Develop automated workflow DAGs in Apache Airflow to orchestrate multi-stage data pipelines
  • Implement modular data modeling using dbt to ensure version-controlled and tested SQL code
  • Execute data quality audits using Great Expectations to identify and mitigate data drift
  • Navigate cloud-native data storage strategies across Snowflake, BigQuery, and Amazon S3 environments
  • Measure pipeline performance using custom KPI dashboards and automated observability alerts
  • Synthesize data engineering workflows with CI/CD practices using Git and automated deployment runners

Requirements & Prerequisites

Participants should have a foundational knowledge of SQL (joins, aggregations) and basic Python programming. Experience with any relational database or cloud platform is recommended but not required. A laptop with Docker Desktop installed is necessary for hands-on exercises.


Professional and Organizational Impact

When you lead data engineering with credible automation and practical strategies, you become a trusted driver of operational agility and analytical precision.

As a professional, you will benefit by:

  • Build technical expertise in modern orchestration tools like Apache Airflow
  • Gain decision-making confidence using data observability and quality metrics
  • Strengthen your professional positioning as a high-demand cloud data specialist
  • Enhance your ability to balance pipeline performance with infrastructure costs
  • Develop production-grade coding skills in Python and advanced SQL
  • Position yourself for leadership roles in analytics engineering and architecture
  • Expand your career reach across global, cloud-first technology organizations

Organizations that embed data engineering excellence into their operational context reduce costs, mitigate risks, and build lasting competitive advantage.

Your organization will benefit from:

  • Reduced operational costs through the automation of manual data preparation tasks
  • Mitigated compliance risks by implementing automated data lineage and governance
  • Improved market positioning through faster delivery of real-time business insights
  • Enhanced data reliability ensuring executive decisions are based on accurate information
  • Scalable infrastructure capable of handling exponential growth in data volume
  • Increased engineering productivity through modular code reuse and CI/CD workflows
  • Minimized data downtime via proactive observability and automated error recovery

Training Methodology

This is a practical, outcome-driven course designed to turn data engineering aspirations into measurable action and credible reporting.

Methodology includes:

  • Hands-on pipeline construction using real-world datasets and cloud-native SQL dialects
  • Scenario simulation requiring incident response to pipeline failures and data quality breaches
  • Data architecture diagnostic using the Well-Architected Framework for data-intensive applications
  • Stakeholder reporting exercise focused on communicating data uptime and pipeline health metrics
  • Case study analysis from the financial services, e-commerce, and healthcare sectors
  • Group workshop producing a functional dbt project with documentation and testing
  • Reflection exercise benchmarking current data practices against the Data Mesh maturity model

Upcoming Sessions

Next available dates worldwide

Virtual

(Zoom) Training
USD 1,700
29th Jun-10th Jul 2026

Nairobi

Kenya
USD 2,900
22nd Jun-3rd Jul 2026

Kigali

Rwanda
USD 3,800
6th Jul-17th Jul 2026

Dubai

United Arab Emirates (UAE)
USD 7,800
27th Jul-7th Aug 2026

Zanzibar

Tanzania
USD 4,300
15th Jun-26th Jun 2026

Abuja

Nigeria
USD 5,880
22nd Jun-3rd Jul 2026

Addis Ababa

Ethiopia
USD 4,900
29th Jun-10th Jul 2026

Mombasa

Kenya
USD 3,200
22nd Jun-3rd Jul 2026

Cape Town

South Africa
USD 7,500
6th Jul-17th Jul 2026

Johannesburg

South Africa
USD 6,000
22nd Jun-3rd Jul 2026

Pretoria

South Africa
USD 5,900
22nd Jun-3rd Jul 2026

Kampala

Uganda
USD 3,700
6th Jul-17th Jul 2026

Lagos

Nigeria
USD 5,250
15th Jun-26th Jun 2026

Certification

Recognized credentials that advance your career

Participants who complete the Data Engineering and Workflow Automation Training Program earn a Trainingcred Certificate of Achievement, demonstrating professional competence and alignment with global standards in learning and development.

NITA Accredited

Accredited by the National Industrial Training Authority, ensuring programs meet nationally recognized standards of quality and relevance.

CPD Certified

Recognized by the CPD Certification Service, ensuring every program meets internationally benchmarked standards of professional excellence.

Why this course earns its place on your CV

Accredited training, practitioner trainers, and peers on the same career track — the three things real expertise is built on.

Skills Relevance

  • Master cutting-edge tools for big data management and automation.
  • Learn to build scalable data pipelines that power modern businesses.
  • Transform raw data into actionable insights with advanced analytics techniques.

Expert Delivery

  • Courses taught by seasoned data engineers from leading tech companies.
  • Gain exclusive industry insights through real-world case studies and examples.
  • Direct mentorship opportunities to guide your learning journey and project work.

Career Advancement

  • Enhance your resume with skills in high demand by top tech employers.
  • Prepare for roles like Data Architect and Automation Engineer with confidence.
  • Access to a professional network of peers and industry leaders.

Real Results from Real Professionals

Thousands of professionals have transformed their careers through our training programs. Now, it's your turn.

Frequently Asked Questions

Got questions? We've gathered the answers to common queries to help you feel confident and informed.

Who else has attended this training course?

Join global leaders and experts from top-tier organizations who have already benefited from this training. Here are just a few of our past participants:

Designation Organization
Project Officer - Data Scientist Misk Foundation, Saudi Arabia
Practitioner Ministry of Mine and Geology, GUINEA
Practitioner Ministry of Mine and Geology, GUINEA
MICRO SOFT ENGINEERING WATOTO, Uganda
Software Developer URWASCO PLC, Kenya
Business Risk Intelligence Analyst Capricorn Group, NAMIBIA

Your seat is waiting.

Join these industry leaders and take the next step in your career.

You will gain hands-on proficiency in Apache Airflow for orchestration, dbt for SQL transformation, and Great Expectations for data quality. Additionally, you will work with cloud-native platforms like Snowflake and containerization tools like Docker.
Yes, this course is designed for intermediate professionals. It bridges the gap by teaching software engineering best practices, Python scripting, and infrastructure management essential for the Data Engineering transition.
Approximately 60% of the course is dedicated to hands-on workshops and exercises. You will build and deploy functional pipelines, DAGs, and data models in a simulated production environment.
You will receive a TrainingCred Professional Certificate in Data Engineering and Workflow Automation. This certificate validates your ability to design and implement production-grade data pipelines using industry-standard tools.
No prior cloud account is required. We provide access to the necessary sandbox environments and localized Docker configurations to ensure all participants can complete the exercises regardless of their current cloud access.

Customize Training Duration

The standard duration for Data Engineering and Workflow Automation Training is 10 Days. The options below are alternative durations with adjusted pricing.

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