What will you learn in Learn Data Engineering Course
Understand the full data engineering lifecycle from ingestion to analytics.
Work with key tools like Kafka, Airflow, Spark, and Snowflake.
Design and build data pipelines using batch and streaming methods.
Handle data transformation, warehousing, and orchestration in real-world scenarios.
Build foundational skills for modern data stacks and cloud-based data workflows.
Program Overview
Module 1: Introduction to Data Engineering
⏳ 1.5 hours
Topics: What is data engineering, role in the data team, lifecycle overview.
Hands-on: Identify components of a modern data stack and project workflow.
Module 2: Ingestion Layer
⏳ 2.5 hours
Topics: Batch vs. streaming ingestion, Kafka basics, file sources, APIs.
Hands-on: Simulate ingestion using Kafka and flat files.
Module 3: Transformation Layer
⏳ 2.5 hours
Topics: Data cleaning, enrichment, ETL vs. ELT, SQL and Python tools.
Hands-on: Build basic transformation logic using pandas and SQL.
Module 4: Orchestration with Airflow
⏳ 2 hours
Topics: DAGs, scheduling, monitoring, retries, dependencies.
Hands-on: Set up and deploy a basic Airflow DAG.
Module 5: Storage and Warehousing
⏳ 2 hours
Topics: Columnar vs. row-based storage, warehouse concepts, intro to Snowflake.
Hands-on: Load data into a Snowflake warehouse and query using SQL.
Module 6: Processing with Spark
⏳ 3 hours
Topics: Spark architecture, RDDs vs. DataFrames, parallelism.
Hands-on: Process large datasets using PySpark.
Module 7: Real-World Project: End-to-End Pipeline
⏳ 3.5 hours
Topics: Combining tools in a real pipeline from source to dashboard.
Hands-on: Build a full pipeline using ingestion, transformation, orchestration, and warehousing.
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Job Outlook
Data engineers are in high demand across industries including tech, healthcare, finance, and e-commerce.
Strong salaries ranging from $100K–$160K+ depending on experience and stack.
Skills in Airflow, Kafka, Spark, and cloud platforms are increasingly sought-after.
Freelance and remote roles growing in data infrastructure and analytics engineering.
Specification: Learn Data Engineering
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