Description

Key Skills: Data Engineering, Python, SQL, PySpark, ETL/ELT, Data Pipelines, Data Lakes, Data Warehouses, Cloud Platforms (Azure/AWS/GCP), Data Processing, Data Quality, Data Integration

Roles & Responsibilities

• Design, develop, and maintain scalable ETL/ELT data pipelines.
• Build data solutions for batch and real-time data processing.
• Develop and manage data lakes, data warehouses, and data marts.
• Create data ingestion frameworks from databases, APIs, files, and streaming sources.
• Optimize data pipelines for performance, scalability, and cost efficiency.
• Implement data quality checks, monitoring, and error handling.
• Collaborate with data architects, data scientists, analysts, and business teams.
• Ensure secure, reliable, and high-performing data solutions.

Experience Required

• 4-12 years of experience in Data Engineering.
• Strong experience with Python, SQL, and PySpark.
• Hands-on experience in ETL/ELT pipeline development.
• Good understanding of data engineering concepts and data workflows.
• Experience with cloud data platforms such as Azure, AWS, or GCP is preferred.
• Knowledge of data quality, performance optimization, and data integration.
• Strong analytical and problem-solving skills.

Education: Any Graduation or Post Graduation in any discipline

Key Skills

Education

Any Graduate