Data Engineer with Python

Key Responsibilities: Design, develop, and maintain scalable data pipelines using Python. Build and optimize ETL/ELT processes to ingest and transform large datasets from multiple sources. Develop and manage data models, data warehouses, and data lakes. Write efficient SQL queries for data extraction, transformation, and analysis. Ensure data quality, integrity, and governance across data platforms. Work closely with data scientists, analysts, and business stakeholders to understand data requirements. Monitor and troubleshoot data pipeline performance issues. Implement data integration solutions using APIs and streaming technologies. Support data visualization and reporting tools such as Power BI or Tableau.

Required Skills: Strong experience with Python for data engineering (Pandas, PySpark, NumPy).Experience building ETL pipelines and data workflows. Proficiency in SQL and relational databases (PostgreSQL, MySQL, SQL Server, etc.).Experience with big data tools such as Apache Spark, Hadoop, or Kafka. Knowledge of data warehousing concepts and data modeling. Familiarity with cloud platforms such as AWS, Azure, or GCP.Experience with version control tools like Git.