Data Engineer (Python)

Role & responsibilities Data Pipeline Development: Design, build, and maintain scalable ETL/ELT data pipelines using PySpark and Python . Process structured and unstructured data from various sources (e.g., APIs, files, databases). Data Integration: Integrate data from internal and external sources into data lakes or warehouses (like AWS S3, Azure Data Lake, or Hadoop HDFS). Database Management: Write optimized SQL queries for data extraction, transformation, and aggregation. Ensure data quality and integrity during ingestion and processing. Preferred candidate profile 8 - 12 years of hands-on experience in Data Engineering or ETL development Strong proficiency in Python , PySpark , and SQL Experience in building and optimizing ETL pipelines for large-scale data Excellent problem-solving and communication skills Ability to work independently and in a team-oriented environment