- AWS (Robust, Mandatory): Extensive hands-on experience with AWS Glue, Athena, EMR, S3, Lambda, and related data services in production environments
- SQL (Strong, Mandatory): Advanced proficiency in writing complex, optimized SQL - joins, window functions, CTEs, query tuning, and performance optimization on large datasets
- Strong experience with Snowflake - data modeling, warehousing, and integration
- Solid understanding of Data Lake architecture and best practices (partitioning, file formats like Parquet/ORC, cataloging)
- Experience with Apache Spark (via EMR) for large-scale distributed data processing
- Proficiency in Python or Scala for ETL scripting (Glue jobs, PySpark)
- Understanding of data warehousing concepts, dimensional modeling, and star/snowflake schemas
- Experience with workflow orchestration tools (AWS Step Functions, Airflow, or similar)
- Familiarity with CI/CD practices for data pipeline deployment
- Strong analytical and problem-solving skills with attention to data accuracy and pipeline reliability

📌 Data Engineer (India)
🏢 TRIGENT SOFTWARE PRIVATE
📍 India