Key Responsibilities

• Design, develop, and optimize ETL and data pipelines for large-scale data processing
• Write and optimize complex SQL queries including joins, subqueries, CTEs, window functions, and performance tuning
• Perform data transformation, validation, cleansing, and data quality checks
• Build and maintain scalable data ingestion pipelines using APIs, SFTP, Kafka, and related integration tools
• Work with large distributed datasets and ensure efficient data processing
• Design and implement graph data models including nodes, edges, and relationships
• Work with RDF data structures and semantic data frameworks
• Develop and optimize SPARQL queries for graph data retrieval and analysis
• Build and maintain knowledge graphs and ontology-driven data systems
• Automate data workflows and operational tasks using Python scripting
• Monitor, troubleshoot, and optimize pipeline performance an...