Python - Data Processing

2–3 years of hands-on experience in Python development. Strong experience with data processing libraries:

Pandas, NumPy

Knowledge of ETL concepts and data pipeline development. Experience working with CSV, JSON, XML, and large datasets. Strong SQL skills and experience with relational databases (e.g., MySQL, PostgreSQL). Experience with API integration and data retrieval. Understanding of data cleaning, validation, and transformation techniques. Basic knowledge of Linux/Unix environments.

Experience with data workflow tools (Airflow, Luigi). Familiarity with big data tools like Spark or Hadoop. Exposure to cloud platforms (AWS, Azure, or GCP). Knowledge of version control systems (Git). Basic understanding of data warehousing concepts.