Results-oriented Data Engineer with 3+ years of experience designing and optimizing scalable ETL pipelines and big data solutions using AWS and PySpark. Skilled in building data lakes, processing large-scale datasets, an…
Results-oriented Data Engineer with 3+ years of experience designing and optimizing scalable ETL pipelines and big data solutions using AWS and PySpark. Skilled in building data lakes, processing large-scale datasets, and improving pipeline performance. Experienced in delivering reliable, high-quality data for analytics and business intelligence. Currently in Dubai and available for immediate joining.
Designed and built ETL pipelines processing 5M+ records daily, ensuring high data accuracy and availability.
Developed scalable Python-based data pipelines and REST API ingestion systems processing 100K+ records/hour for batch and real-time workflows.
Validated and tested Delta Lake tables in Databricks for batch and incremental ETL pipelines, ensuring 99% data accuracy.
Optimized Apache Spark jobs, reducing execution time by 25–30% and improving resource utilization.
Optimized ETL workflows and SQL queries, reducing data processing time by 30%.
Automated workflows using Python and AWS Step Functions, reducing manual effort by 40%.
Collaborated with cross-functional teams, improving system performance and reducing downtime by 20%.
Improved database performance by optimizing queries and indexing strategies, reducing execution time by 30%.
Designed and built ETL pipelines processing 5M+ records daily, ensuring high data accuracy and availability., Developed scalable Python-based data pipelines and REST API ingestion systems processing 100K+ records/hour for batch and real-time workflows., Validated and tested Delta Lake tables in Databricks for batch and incremental ETL pipelines, ensuring 99% data accuracy., Optimized Apache Spark jobs, reducing execution time by 25–30% and improving resource utilization., Optimized ETL workflows and SQL queries, reducing data processing time by 30%., Automated workflows using Python and AWS Step Functions, reducing manual effort by 40%., Collaborated with cross-functional teams, improving system performance and reducing downtime by 20%., Improved database performance by optimizing queries and indexing strategies, reducing execution time by 30%.
Processed and validated 50K+ records daily using Python and PySpark, improving data quality by 20%.
Developed automation scripts for ETL workflows, improving pipeline efficiency by 20%.
Led testing, debugging, and deployment, reducing data pipeline errors by 20%.
Processed and validated 50K+ records daily using Python and PySpark, improving data quality by 20%., Developed automation scripts for ETL workflows, improving pipeline efficiency by 20%., Led testing, debugging, and deployment, reducing data pipeline errors by 20%.
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