We are seeking a skilled and motivated Data Engineer with 3–6 years of experience to design, build, and maintain scalable data pipelines. The ideal candidate should have strong expertise in PySpark, AWS services, SQL, AWS Glue, and Amazon Redshift. You will play a key role in developing robust data solutions that support analytics and business intelligence initiatives.

Design, develop, and maintain scalable data pipelines using PySpark Build and optimize ETL workflows using AWS Glue Manage and process large datasets efficiently in Amazon Redshift Write complex and optimized queries using SQL Work with various AWS services for data ingestion, transformation, and storage Ensure data quality, integrity, and security across pipelines Collaborate with data analysts, data scientists, and cross-functional teams Monitor, troubleshoot, and improve existing data workflows and pipelines Implement best practices for data engineering, performance tuning, and cost optimization

trong hands-on experience in PySpark Proficiency in AWS cloud services (S3, Glue, Redshift, etc.) Expertise in SQL (query optimization, performance tuning) Experience with AWS Glue for ETL development Strong knowledge of Amazon Redshift data warehousing Good understanding of data modeling and data architecture Familiarity with big data processing concepts