ETL Development with Airflow Course: Orchestrating Workflows for Scalable Data Operations

Introduction

In the era of big data, organizations increasingly depend on efficient data pipelines to move, transform, and prepare data for analytics and business intelligence. As enterprises scale their digital ecosystems, managing Extract, Transform, Load (ETL) processes becomes critical for ensuring that data flows are automated, reliable, and cost-effective. This course equips participants with cutting-edge knowledge and practical skills in ETL development using Apache Airflow, the industry-leading workflow orchestration tool.

The training begins by introducing the foundations of ETL design and the role of workflow orchestration in modern data engineering. Learners will explore the challenges of traditional ETL processes and how Airflow provides a scalable, flexible, and extensible framework to streamline complex data operations.

Participants will gain hands-on experience in designing Directed Acyclic Graphs (DAGs), scheduling workflows, integrating Airflow with diverse data sources, and ensuring data reliability at scale. With real-world use cases, the course emphasizes building resilient, fault-tolerant pipelines that support business-critical decision-making.

A strong focus is placed on emerging practices, such as orchestrating cloud-native data operations, integrating Airflow with Spark and BigQuery, leveraging containerized deployments with Kubernetes, and ensuring observability through monitoring and logging frameworks. These skills ensure participants can confidently operate in modern enterprise data ecosystems.

By the end of this program, learners will not only be proficient in ETL pipeline development but will also be equipped to manage scalable, automated, and efficient workflows that empower organizations with timely, high-quality data.

Who Should Attend

• Data engineers and ETL developers.
• Data architects responsible for pipeline design.
• BI developers and analytics engineers.
• IT professionals working with big data infrastructure.
• Cloud engineers managing data workflows.
• Database administrators overseeing data flows.
• Software engineers exploring data engineering roles.
• Data scientists requiring reliable pipelines for analytics.
• Consultants in enterprise data operations.
• Project managers overseeing data-driven initiatives.

Duration

5 days

Course Objectives

By the end of this course, participants will be able to:

• Understand the role of ETL in modern data engineering.
• Design and implement ETL workflows using Apache Airflow.
• Build and schedule DAGs for complex data pipelines.
• Automate data extraction from diverse sources.
• Apply transformations to ensure data quality and consistency.
• Load structured and unstructured data into data warehouses.
• Integrate Airflow with Spark, Hadoop, and cloud services.
• Implement observability with logging, monitoring, and alerting.
• Deploy Airflow pipelines in scalable and fault-tolerant environments.
• Optimize performance and ensure operational efficiency of ETL systems.

Comprehensive Course Outline

Module 1: Introduction to ETL and Workflow Orchestration

• Fundamentals of ETL processes and data pipelines.
• Challenges of traditional ETL frameworks.
• Role of Apache Airflow in workflow automation.
• Overview of DAGs, operators, and task dependencies.

Module 2: Airflow Architecture and Setup

• Core components of Apache Airflow.
• Installation and configuration best practices.
• Scheduler, executor, and worker concepts.
• Running Airflow on local and cloud environments.

Module 3: DAG Design and Scheduling

• Creating Directed Acyclic Graphs (DAGs).
• Scheduling workflows with cron expressions.
• Task dependencies and parallel execution.
• Error handling and retry strategies.

Module 4: Data Extraction Techniques

• Connecting to databases and APIs.
• Extracting data from structured and unstructured sources.
• Batch vs. streaming extraction methods.
• Security and authentication for external systems.

Module 5: Data Transformation and Quality

• Designing scalable transformation workflows.
• Data cleansing and enrichment strategies.
• Schema evolution and validation techniques.
• Ensuring consistency across multiple data sources.

Module 6: Data Loading into Warehouses and Lakes

• Loading strategies for relational databases.
• Loading into cloud data warehouses (Snowflake, Redshift, BigQuery).
• Integration with data lakes (S3, HDFS).
• Best practices for partitioning and optimization.

Module 7: Integrations with Big Data and Cloud Ecosystems

• Orchestrating Spark jobs with Airflow.
• Integration with Hadoop and Hive.
• Using Airflow with Kubernetes and Docker.
• Cloud-native orchestration with AWS, Azure, and GCP.

Module 8: Monitoring, Logging, and Observability

• Setting up Airflow monitoring dashboards.
• Logging strategies for debugging pipelines.
• Alerting and notification mechanisms.
• Ensuring pipeline reliability with observability tools.

Module 9: Scaling and Deployment Strategies

• Scaling Airflow with Celery and Kubernetes executors.
• High-availability deployment models.
• Versioning and CI/CD integration.
• Managing performance at enterprise scale.

Module 10: Future of ETL and Workflow Orchestration

• Airflow in the era of real-time data pipelines.
• Integration with data mesh and microservices.
• AI-driven pipeline orchestration.
• Emerging alternatives and hybrid orchestration models.

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: training@upskilldevelopment.com Tel: +254 721 331 808

Training Venue

The training will be held at our Upskill Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Upskill certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: training@upskilldevelopment.com, +254 721 331 808

Terms of Payment

Unless otherwise agreed between the two parties payment of the course fee should be done 3 working days before commencement of the training so as to enable us to prepare better