Mahesh Peiris
I started my career as a Financial Data Analyst, building SQL and Python data pipelines and supporting financial reporting and data quality within Finance-owned BigQuery tables. Over the past several years that scope has evolved significantly into platform engineering, infrastructure automation, data engineering, and production operations — with growing ownership of the cloud infrastructure, Kubernetes environments, and CI/CD systems supporting automation and AI-related initiatives. My current work combines data engineering, cloud infrastructure, Kubernetes, and production platform ownership.
Experience
Platform & Data Engineer
Originally hired as a Financial Data Analyst, my role has expanded into platform engineering, infrastructure automation, and production operations supporting Finance's automation and AI-related initiatives.
- Infrastructure & Platform Engineering — Design, provision, and manage cloud infrastructure using Terraform for scalability, reliability, and cost-efficiency across environments; design and maintain production-grade Kubernetes environments for cloud-native workloads; work with Change Approval Board (CAB), Security, and IT teams to review and safely implement infrastructure changes.
- Kubernetes & Workload Orchestration — Configure and manage Deployments, Services, ConfigMaps, and CronJobs for scheduled data ingestion; build and maintain Helm charts for consistent, version-controlled deployments; implement GitOps workflows with Argo CD.
- Data Pipelines & Event-Driven Architecture — Design and implement ETL workflows for ingestion, transformation, and aggregation across external platforms; build and maintain Pub/Sub-based workflows for asynchronous, event-driven data ingestion; support scalable AI/ML data processing pipelines.
- Database & Application Operations — Design, manage, and optimize PostgreSQL and Google BigQuery for high availability, data integrity, and performance; deploy and manage user-facing applications on Kubernetes, including financial web platforms; troubleshoot production incidents and drive root-cause analysis.
- CI/CD & Automation — Design end-to-end CI/CD pipelines for build, test, and deployment automation; integrate source control, automated testing, and deployment workflows; automate recurring operational tasks with Python and Shell scripting.
- Integration & Reliability Engineering — Build and maintain REST API-based ingestion pipelines connecting third-party platforms; set up monitoring, alerting, and centralized logging; establish ongoing incident response practices.
- Cross-team Collaboration — Partner with AR, AP, FDA, and other Finance teams to identify automation opportunities and reduce manual effort across the division.