Monish Ritvik

• Experienced Data Engineer with 12+ years of strong background in building scalable and reliable data pipelines across cloud platforms.
• Expertise in Data warehouses like Azure synapse, analytics, redshift, snowflake ,Big query for data modeling, performance optimization, and query tuning.
• Proficient in Apache Spark and Spark for large-scale data processing and transformation tasks.
• Hands-on experience with Databricks for collaborative development, orchestration, and ML workflows.
• Built and maintained ETL/ELT pipelines using tools like Apache Airflow, DBT, and Azure Data Factory, AWS glue, Cloud composer.
• Designed modern data architectures leveraging data lake houses on Delta Lake.
• Worked with structured, semi-structured, and unstructured data using JSON, Parquet, and Avro formats.
• Built robust ingestion pipelines using Kafka, AWS Kinesis, and Azure Event Hubs for real-time processing.
• Automated data workflows and infrastructure using Terraform, CloudFormation, and CI/CD pipelines.
• Implemented SCD (Slowly Changing Dimensions) and CDC (Change Data Capture) strategies using DBT and Five Triggers.
• Deployed scalable solutions on AWS (S3, Redshift, Glue, Lambda), Azure (Data Lake, Synapse, Functions), and GCP (Big Query, Cloud Functions).

• Experienced Data Engineer with 12+ years of strong background in building scalable and reliable data pipelines across cloud platforms.
• Expertise in Data warehouses like Azure synapse, analytics, redshift, snowflake ,Big query for data modeling, performance optimization, and query tuning.
• Proficient in Apache Spark and Spark for large-scale data processing and transformation tasks.
• Hands-on experience with Databricks for collaborative development, orchestration, and ML workflows.
• Built and maintained ETL/ELT pipelines using tools like Apache Airflow, DBT, and Azure Data Factory, AWS glue, Cloud composer.
• Designed modern data architectures leveraging data lake houses on Delta Lake.
• Worked with structured, semi-structured, and unstructured data using JSON, Parquet, and Avro formats.
• Built robust ingestion pipelines using Kafka, AWS Kinesis, and Azure Event Hubs for real-time processing.
• Automated data workflows and infrastructure using Terraform, CloudFormation, and CI/CD pipelines.
• Implemented SCD (Slowly Changing Dimensions) and CDC (Change Data Capture) strategies using DBT and Five Triggers.
• Deployed scalable solutions on AWS (S3, Redshift, Glue, Lambda), Azure (Data Lake, Synapse, Functions), and GCP (Big Query, Cloud Functions).

2011 passed out  - bachelors - electronics and communications - veltech university 
2013 passed out - masters - informations systems - pace university