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Addressed challenges in real-time data retrieval between the Fraud Detection multi-node cluster and its Anti-Money Laundering (AML) extension enabling faster fraud case expansion for analysts • Developed and maintained CI/CD pipelines automating integrations between the Fraud Detection tool, Directory Services (LDAP), and AML application. Streamlined deployment on both VMs and Kubernetes clusters, cutting deployment time from ~2 hours to 25 minutes and reducing integration errors by ~70 % • Integrated Apache JMeter scripts into CI/CD workflows to simulate concurrent user loads and traffic spikes. This provided pre-deployment performance insights, decreasing production latency issues by ~25 % and improving confidence in release readiness • Implemented an ETL pipeline to extract and standardize transaction data from distributed event-streaming systems for warehousing and dashboard analytics which enabled real-time visibility into thousands of events per hour • Administered Identity and Access Management (IAM) using Role-Based Access Control (RBAC) and least-privilege principles which strengthened infrastructure security posture and cut access- related incident tickets by ~60 % • Optimized database configuration and schema updates for the AML application to improve responsiveness which achieved faster query performance • Managed version control systems and enforced security best practices across development environments which reduced code exposure risk and ensured consistent compliance with internal DevSecOps policies • Integrated legacy banking systems with the Fraud Detection cluster via secure API enhancing interoperability ensuring reliable multi-system communication • Led cross-functional collaboration with developers, cybersecurity analysts, and business stakeholders to troubleshoot production challenges which shortened issue triage time by ~30 % and improved delivery predictability across teams • Conducted incident investigations and developed incident-response playbooks. Lowered mean-time-to-recovery (MTTR) by ~25 %, improving overall system availability to 99.9 %. • Deployed AML applications in client environments and handled post-deployment customer support and root-cause analysis. Reduced repeated field incidents by ~50 % within two release cycles and improved client satisfaction scores. Technologies: AWS (IAM, S3, EKS) | ArgoCD | Jenkins | MongoDB | LDAP | Nginx | Cloudflare | Kafka | Apache Jmeter | SonarQube | Git | Redis | GitGuardian | NFS | Terraform | Ansible | Grype | Docker Language (Frameworks): Typescript (Nestjs, Reactjs)

Designed autoscaling EC2 clusters with Terraform, Ansible and Packer, cutting manual provisioning time by 60 % • Built and deployed autoscaling Kubernetes (EKS) clusters from scratch with Terraform, ensuring horizontal scalability and 99.9 % service uptime • Automated provisioning and configuration management with Terraform, Ansible, and CloudWatch, reducing manual server setup and configuration drift • Reverse-engineered legacy environments using Terraformer, migrating unmanaged infrastructure into version-controlled IaC, achieving 100 % environment reproducibility and faster disaster recovery • Developed reusable Ansible playbooks for Ubuntu and RHEL servers, accelerating server configuration cycles from hours to minutes and reducing human error by 70 % • Authored Bash scripts for monitoring, log rotation, and deployment tasks, improving system reliability and reducing recurring operational incidents by 30 % • Engineered a full CI/CD pipeline with Jenkins, GitHub, Ansible, Artifactory, and SonarQube, cutting deployment time from 60 min to 10 min and improving code quality through automated testing and analysis • Wrote detailed technical documentation for project implementation steps and CI/CD pipelines, reducing onboarding time for new engineers • Provided Tier-2 technical support for internal teams, resolving deployment and environment issues with an average resolution time improvement of 40 %. Technologies: AWS (S3, IAM, EKS, ECR, RDS, Route 53, Secrets Manager, ELB, ASG, VPC, DynamoDB, CloudWatch) | GCP (Compute Engine, GKE) | Jenkins | MongoDB | Nginx | Apache | Artifactory | MySQL | Packer | SonarQube | Git | GitGuardian | Terraform | Ansible | Grype | Docker | Helm Languages/Frameworks: PHP (Laravel), JavaScript (Express.js, React.js, Angular.js)

Collected and analyzed usage data to ascertain project feasibility and profitability within a 6-month deadline. Liaised with engineers and architects to synergize designs and operational requirements towards optimizing designs for maximum functionality of development project. Worked with cloud consultants and solutions architect, software development unit and IT business analysis unit on the design of turnkey IT solutions to manage different aspects of operation and design.

Conducted primary consumer and customer research studies to drive consumer-centric marketing which boosted sales by 23% in the organization. Used database languages such as SQL to extract data from data warehouses, processed and analysed complex data sets using advanced querying, visualization and analytics tools. Converted raw data and findings into presentable and understandable tables, graphs, infographics, visuals and written reports to management and non-technical personnel such as clients. Measured the effectiveness of marketing programs and strategies by tracking success/failure rates using quantifiable metrics. Created predictive reports using structured and unstructured data and findings to envisage market events that may affect sales.