Vikrant Nalawade
Data Engineer (4+ YOE) | Python, SQL, AWS |
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About
Data Engineer with 4+ years of experience designing and optimizing scalable batch & real-time data pipelines using Python, SQL, PySpark, Spark Streaming, Hadoop, and Kafka. Hands-on expertise in AWS Glue, EMR, S3, Lambda, Athena, and Airflow orchestration for building reliable, production-grade ETL/ELT workflows. Skilled in data modeling (OLTP, OLAP, SCD Type 2, partitioning, CDC) and designing Data Lakes & Warehouses for high-performance analytics.
Key achievements
- Built pipelines processing 100TB+ weekly with PySpark, Kafka & AWS.
- Developed streaming pipelines for 1M+ daily users across 30+ sources, reducing latency from hours to minutes.
- Optimized legacy ETL workflows, achieving 35% faster runtime and saving ~$10K/quarter.
- Designed reusable ingestion frameworks (APIs, SFTP) reducing onboarding time by 50%.
- Immediate Joiner | Seeking opportunities to design & scale real-time data platforms on AWS & Spark, with an interest in financial/quantitative systems.
Experience
Data Engineer with 4+ years of experience designing and optimizing scalable batch & real-time data pipelines using Python, SQL, PySpark, Spark Streaming, Hadoop, and Kafka. Hands-on expertise in AWS Glue, EMR, S3, Lambda, Athena, and Airflow orchestration for building reliable, production-grade ETL/ELT workflows. Skilled in data modeling (OLTP, OLAP, SCD Type 2, partitioning, CDC) and designing Data Lakes & Warehouses for high-performance analytics.
Key achievements
- Built pipelines processing 100TB+ weekly with PySpark, Kafka & AWS.
- Developed streaming pipelines for 1M+ daily users across 30+ sources, reducing latency from hours to minutes.
- Optimized legacy ETL workflows, achieving 35% faster runtime and saving ~$10K/quarter.
- Designed reusable ingestion frameworks (APIs, SFTP) reducing onboarding time by 50%.
- Immediate Joiner | Seeking opportunities to design & scale real-time data platforms on AWS & Spark, with an interest in financial/quantitative systems.
