Lecture Notes: Role and Skills of a Data Engineer

Introduction to Data Engineering

• Importance of Data Engineers in AI-based companies.
• Data Engineers facilitate decision-making by providing data.
• They gather data from various sources required for projects.

Role of a Data Engineer

• Primary Task: Bring data from multiple sources.
  • Sources can include SQL databases, APIs, cloud storage, websites, and IoT sensors.
• Objective: Convert data into useful formats.

ETL and ELT Processes

• Traditional Process: ETL (Extract, Transform, Load)
  • Extract and transform data, then load it.
• Modern Process: ELT (Extract, Load, Transform)
  • Adapt based on data size:
    • Big Data: Load first, then transform.
    • Normal Data: Transform first, then load.

Essential Skills for a Data Engineer

Programming Skills

• Master at least one programming language.
• Learn basics of a second programming language.

Data Pipeline Construction

• Unique skill for data engineers: building data pipelines.
• Learn Apache Spark and Airflow from scratch.

Database Management

• Experience with various databases:
  • SQL, MySQL, PostgreSQL.
  • Tools for handling databases: Snowflake, BigQuery, Redshift.

Understanding Cloud and Big Data

• Familiarity with cloud technology:
  • AWS, GCP (Google Cloud Platform), Azure.
• Essential for handling big data processes.

Version Control and Data Modeling

• Learn Git and GitHub for version control.
• Data modeling with tools like Snowflake.

Career Outlook for Data Engineers

• Expected salary for freshers with these skills: 6 LPA to 12 LPA.
• Strong foundation in these skills is essential for starting a career in data engineering.