Overview
During my extended term at TD Bank, I worked across data engineering, platform automation, infrastructure operations, and internal process improvement. My primary contributions included building a production ADF automation solution, decommissioning unused Analytical Zone infrastructure, and improving the DevSecOps request intake workflow.
Work
PSS Kill Query Automation
- Designed, built, tested, and deployed an end-to-end Azure Data Factory automation pipeline from scratch to production.
- Developed supporting T-SQL queries, stored procedures, sequences, views, logging, and database objects.
- Automated Synapse Pool health monitoring, query analysis, escalation, and controlled session termination.
- Implemented centralized execution and failure logging to improve observability and troubleshooting.
- Managed ADF and Azure SQL database deployment across development, testing, and production environments.
- Reduced reliance on manual monitoring and ad-hoc investigation, helping lower Mean Time to Detect (MTTD) and Mean Time to Resolve (MTTR).
- Created operational documentation and runbooks to support handoff and ongoing operation by the PSS team.
Analytical Zone Decommissioning
- Decommissioned 15 Analytical Zones that had reached Client Validation or Complete status but remained pending due to operational bottlenecks.
- Investigated the infrastructure, resources, dependencies, and architecture supporting Analytical Zones to safely complete teardown activities.
- Coordinated and validated decommissioning across affected infrastructure.
- Delivered approximately $394K in tracked infrastructure cost savings / cost avoidance.
DevSecOps Intake Form Refinement
- Refined the DevSecOps request intake process after stakeholders identified fragmented forms, unclear requirements, frequent returned requests, and poor end-user usability.
- Consolidated and clarified intake forms to make required information easier for users to understand and submit correctly.
- Worked with Confluence and ConfiForms to improve form structure, documentation, and request workflows.
- Reduced unnecessary back-and-forth, incomplete submissions, and operational effort required to process requests.
Stack
- Cloud: Microsoft Azure
- Data Engineering: Azure Data Factory, Azure Synapse Analytics, Azure SQL
- Database: T-SQL, stored procedures, sequences, views
- DevOps: Git, CI/CD, multi-environment deployment
- Documentation & Workflow: Confluence, ConfiForms
- Core Areas: Pipeline orchestration, SQL development, production deployment, monitoring, troubleshooting, infrastructure decommissioning, operational automation, process improvement