Kirtan is a Data Engineer with 7+ years of experience in data engineering, specializing in AWS, Python, and data pipeline optimization. He has a proven track record of leading teams and delivering scalable data solutions.
Successfully migrated 10 TB of data to Amazon Redshift with zero downtime.
Architected and implemented robust real-time data ingestion pipelines using AWS IoT Core and AWS Kinesis.
Led data processing initiatives using DBT and Airflow for end-to-end workflow optimization.
Integrated data from 50+ APIs and 5+ file storage locations, automating ingestion workflows.
Overview: Led a strategic migration from a legacy on-premises data warehouse to Amazon Redshift to enhance scalability, performance, and cost-efficiency. Responsibilities: Defined migration strategy and roadmap, assessed data compatibility and performance requirements, optimized ETL pipelines for cloud-native environment using AWS Glue.
Key outcomes:
Successfully migrated 10 TB of data to Amazon Redshift with zero downtime.
Achieved significant performance improvements and cost reductions.
Overview: Developed a scalable real-time data pipeline to optimize fuel consumption within a glass factory by leveraging various sensors' data. Responsibilities: Architected and implemented a robust real-time data ingestion pipeline using AWS IoT Core and AWS Kinesis.
Key outcomes:
Optimized fuel consumption within a glass factory.
Successfully processed and stored high-volume data.
Overview: Led initiatives to optimize the end-to-end data engineering workflow, focusing on efficiency and automation. Responsibilities: Utilized DBT for data processing and testing, and Airflow for orchestration, ensuring seamless data flow from raw to aggregated layers.
Key outcomes:
Optimized end-to-end data engineering workflow.
Enhanced workflow automation and data integration using Airflow and DBT.
Key outcomes:
Developed a scalable, efficient, and cost-effective data migration framework.
Ensured minimal downtime and data integrity during transitions.
Maintained historical accuracy and data integrity using CDC and SCD.
Scalable Data Pipeline for Customer Data — Salesforce + JIRA + AppInsights to data lake.
Key outcomes:
Successfully integrated data from multiple sources (Salesforce, JIRA, AppInsights).
Enhanced data quality through advanced cleaning and preprocessing.
Provided data for a customer churn prediction model.
Kirtan
Data Engineer