Built Infrastructure-as-Code using Terraform to provision AWS platform infrastructure.

Implemented AWS networking components including VPCs, subnets, route tables, internet gateways, NAT gateways, and security groups.

Designed IAM roles and permission policies to enable secure access for platform services and engineering teams.

Implemented observability infrastructure using CloudWatch dashboards, log groups, and metric alarms for platform monitoring.

Created an EC2 onboarding and connection guide documenting the process for engineers to securely access and manage EC2 instances.

Supported application availability and reliability by setting up and maintaining local development environments using XAMPP, troubleshooting configuration issues, and ensuring stable application operation during development and testing.

Assisted with system maintenance tasks including configuration changes, updates, and validation of application behavior.

Monitored application behavior and user-facing functionality during development, identifying issues early and collaborating with team members to troubleshoot and resolve defects efficiently.

Contributed to documentation of setup procedures, configuration steps, and troubleshooting guidelines to support team operations.

Built and customized forms and UI components using plugins, shortcodes, and CSS.

Designed and managed data pipelines that collect, process and analyze data from fire safety systems.

Managed AWS infrastructure including S3, Lambda, and EC2 for scalable workloads.

Created CI/CD pipelines with GitHub Actions for seamless deployments.

Developed data models and implemented storage solutions to support analytics for fire risk assessments, maintenance schedules and incident reporting.

Created and tested frameworks to validate the performance and reliability of data-driven solutions, including machine learning models.

Automated 20+ ETL/ELT jobs using Airflow and GCP (BigQuery, GCS, Pub/Sub).

Improved job reliability and reduced manual intervention by over 70%.

Modeled analytics-ready data marts with dbt, consolidating data from 7+ sources.

Developed data pipelines with Python/SQL, improving accuracy by 15% and processing efficiency by 50%.

Deployed containerized ML workloads in Kubernetes and Docker, supporting reproducibility and scalable inference.

Contributed to ML models for electrification prediction (95% accuracy), enabling better business resource allocation.

Manage and optimize databases to ensure high performance, availability, and reliability.