As a Cogito Systems Technical Solutions (TS) Engineer at Epic Systems, I provide managerial and technical support for Epic's Cogito reporting infrastructure at 5 healthcare organizations, and I work on internal pods to improve areas of the Cogito applications.
As a Cogito Systems TS, my primary responsibility is supporting the Epic reporting infrastructure for 5 healthcare organizations across the US. This involves delivering compassionate service to proactively solve issues and adapt to customer's needs. I keep them updated on Epic RDBMS best practices, guide them through upgrade issues, and work with R&D to share feedback and coordinate fix and enhancement development. In addition, I provide annual hardware sizing for organization's RDBMS server specifications to guide CIO purchasing decisions.
During Q1 of 2022 I coordinated a customer's Epic upgrade by working with key stakeholders and organizing over 30 Epic TS. This primarily involved collaborating with the organization's Epic upgrade project manager on timelines, going through release procedures, keeping TS updated, and escalating potential upgrade issues. They successfully upgraded in early April.
Since August 2021 I have been a Team Lead on Cogito Systems where I have directly managed 2 team members. I have helped develop and grow their technical and service skills for customer work and handled difficult conversations. In addition I engage in application-level discussions to influence the direction of Cogito Systems TS support. Most recently sharing insight on customers struggling with ETL performance to revamp the at-risk process, which is used to track and guide customers that could have more successful reporting infrastructure.
I lead a team of 10 Cogito Systems TS with the goal of improving the performance and scalability of the Epic suite of applications for all customers. The primary performance KPI is the success of the Caboodle ETL, or daily data transfer from the operational database to Epic's enterprise data warehouse (Caboodle). As the pod lead I managed multiple analytical and service related projects and processes to improve the KPI; including improving internal troubleshooting documentation, developing SQL queries to analyze trends in customer and table ETL performance, preparing a biweekly executive summary on ETL performance, and connecting with R&D to guide development priorities. I presented to the over 80 Cogito Systems TS on performance investigation steps and expectations to build process awareness and encourage a culture of proactive performance investigation.
I participated in the Cogito cloud pod to test cloud products and build relationships with cloud vendors to better support healthcare organizations interested in moving their reporting infrastructure to the cloud. I developed an internal tool to track customers who expressed an interest in moving to the cloud as a reference for leadership and to easily determine what are the primary customer interests.
I built an internal Azure Cogito testing environment and developed PowerShell scripts to automate an ETL load simulation and measure virtual machine (VM) performance. The goal was to provide accurate customer compute sizing guidance so they can be successful while minimizing cost. I specifically worked on developing a cloud processor efficiency rating, and comparing different Azure offerings such as core-constrained VMs, or VMs with hyperthreading turned off. I also partnered with Microsoft to interpret the results and share feedback.