VRINDA MOHAN

Client: Natwest, U.K

Natwest Applications focus on Transaction Monitoring to generate alerts by consuming data from a number of source systems. Its purpose is to identify anomalous and suspicious customer behaviour based on their transactional activities as part of batch processing

• Worked with Google Cloud Platform (GCP) services such as Compute Engine, Cloud Storage, Dataflow, Dataproc, Kubernetes Engine, and Cloud Monitoring to monitor and manage the application
• Scheduled, monitored, and resolved issues for batch jobs in Autosys, ensuring seamless execution and adherence to production timelines
• Regularly reviewed and updated JIL files to enhance batch performance
• Handled incident and change management within ServiceNow, ensuring swift resolution of incidents ahead of SLA targets, managing change requests, and maintaining comprehensive documentation to ensure process management and compliance
• Utilized Google Dataflow to process and transform data from various source systems to parquet format, ensuring end-to-end data validation and handled real-time monitoring of ETL jobs in Dataproc
• Leveraged Apache Spark (Scala) and executed basic queries to analyze large datasets and assist in business analysis
• Created and maintained GCP dashboards to analyze and monitor the performance of virtual machines, tracking CPU, memory, and disk utilization to ensure optimal resource allocation and system performance
• Handled the monitoring of Connect Direct jobs scheduled via CA7, proactively resolving issues and ensuring smooth data transfers between systems
• Familiarized with Gitlab pipelines, Elasticsearch and Jira to assist in basic tasks
• Conducted root cause analysis of recurring incidents, gathering customer and stakeholder feedback to enhance service delivery, and coordinating with cross-functional teams to deploy quick fixes