John Kuloth Petersan S Email and Phone Number

• Developed automation tasks using Python script for NiFi Registry, ensuring seamless recovery of all tasks during the migration of NiFi into Kubernetes.• Designed and implemented an Airflow DAG using KubernetesPodOperator, improving data pipeline efficiency by 25%.• Contributed to Backstage by enhancing the microservice ecosystem with comprehensive documentation for 10+ microservices, increasing developer onboarding speed by 30%.• Implemented CI/CD processes using GitHub Actions with ArgoCD and Helm chart, facilitating seamless deployment of 15+ microservices into GCP Kubernetes.• Worked with dbt (data build tool) for data preparation, transforming raw data into organized and meaningful formats, reducing data processing time by 50%.Carbon Emission Insights: • Developed end to end Carbon Emission Insights Dashboard project using Python for data processing, Apache Airflow for job orchestration, DBT for data transformation, and Tableau for visualization. • Quantified CO2e emissions across various shipment methods and used Tableau to create interactive dashboards with comparative charts and geographical maps. • Facilitated informed decision-making for optimizing logistics strategies towards sustainability and reducing environmental impact.Enterprise Data Integration:• Designed and implemented a data pipeline to extract, transform, and load shipment data from GCP to Snowflake, ensuring efficient data processing and integration.• Integrated with the SeaRoutes Shipment API to enrich shipment data with carbon emission metrics, managing API call concurrency and handling errors effectively.• Automated data loading into Snowflake using SnowPipe, robust error handling, and reprocessing of failed shipments to maintain data integrity and accuracy.

Client: Humana• Designed and developed ETL (Extract, Transform, and Load) jobs using SSIS to integrate data from Archer (Business Application) into MSSQL, processing 10GB+ of data daily.• Created and managed SSIS packages to handle data extraction, cleansing, transformation, and loading tasks efficiently and accurately.• Designed tables and optimized complex stored procedures to facilitate data retrieval, manipulation, and reporting, contributing to a 35% improvement in database performance and response times.• Optimized SSIS packages for performance and scalability, ensuring efficient data processing and reducing ETL job run times by 40%.• Created monitors, alarms, notifications and logs for Lambda functions, Glue Jobs, EC2 hosts using CloudWatch and used AWS Glue for the data transformation, validate and data cleansing. • Worked with S3, AWS, EC2 Machine, etc. and extracting the data from the different sources and the Redshift database and Create Glue jobs in AWS and load data to S3 staging area and persistence area.• Involved in developing data pipelines using AWS (EMR, EC2, S3, RDS, Athena, Lambda) and moving large scale pipeline applications from on premise clusters to AWS cloud.• Involved in creating event driven ETL pipelines by using AWS Glue whenever new data is appeared on AWS S3 and understand data assets.• Worked with AWS Athena to perform analytics on the data stored in S3 buckets.