SQL & Database Management – The Core of Data Engineering: Proficiency in SQL and understanding relational and NoSQL databases is foundational for querying, storing, and managing data effectively.
ETL Pipelines – Extract, Transform, Load Mastery: Building efficient ETL pipelines is critical for moving and transforming data across systems in a scalable and reliable way.
Data Warehousing – Structured Data Storage Expertise: Knowledge of platforms like Snowflake, BigQuery, or Redshift is key for organizing and analyzing large datasets.
Programming Skills – Python & Scala in Demand: Python and Scala are widely used for scripting, data manipulation, and integrating with big data frameworks like Spark.
Cloud Platforms – AWS, GCP & Azure Proficiency: Familiarity with cloud services for data storage, processing, and orchestration is a must-have for modern data engineers.