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Rutuja Shelke

@rutujashelke

I build reliable, cost-efficient AWS data pipelines and analytics-ready warehouses using PySpark, Redshift, Airflow, Snowflake, and dbt.

India

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What I'm looking for

I'm looking to build reliable, scalable cloud data platforms, improve data quality and warehouse performance, and deliver analytics-ready datasets using AWS, Snowflake, dbt, and orchestration tools.

I build cloud-native data platforms on AWS, delivering batch and real-time ETL/ELT pipelines with AWS Glue, PySpark, Amazon S3, AWS DMS, Redshift, Athena, Lambda, and Apache Airflow.

At Network Techlab India Pvt Ltd, I designed scalable pipelines, migrated legacy XML, Shell Script, and IBM DataStage workflows to AWS, and implemented Bronze, Silver, and Gold Medallion Architecture layers for business reporting. I also reduced Redshift query execution time by 40% through sort key tuning, distribution optimization, and automated vacuum/analyse routines.

I've built event-driven workflows with SNS, SQS, Lambda, and S3 events, alongside data quality validation frameworks and CloudWatch monitoring to improve production reliability.

My project work includes CDC-based migration into Redshift with AWS DMS and Glue, as well as a booking analytics ELT pipeline using AppFlow, Snowflake, and dbt to produce tested incremental fact and dimension models.

Experience

Work history, roles, and key accomplishments

Data Engineer

Network Techlab India Pvt Ltd

Sep 2024 - Apr 2026 (1 year 7 months)

Designed and maintained scalable ETL/ELT pipelines using AWS Glue (PySpark), Amazon S3, AWS DMS, Redshift, Athena, and Lambda, orchestrated via Apache Airflow. Implemented event-driven architectures, migrated legacy ETL workflows, and engineered Medallion Architecture layers.