Dynamic Computing Srvies/Accenture
March 2020 - August 2023Data Enginer/ETL developer
Deploy Data warehouse for Texas Medicaid using Oracle ETL, Linux shell scripting and Active Batch Job scheduling. Main duties are Code maintenance, troubleshooting and improvement in agile development life cycle.
SAMSUNG AUSTIN SEMICONDUCTOR
November 2013 - January 2020Systems Engineer
Support of the MES (Manufacturing Execution System) factory automation system, including its logic business rules and UI. Acquiring extensive experience in oracle PL/SQL, unix scripting, Splunk, rendezvous (Tibco RV) bus communication, troubleshooting complex source codes, and exposure to software development cycle
Final Phase Systems
December 2010 - October 2013Systems Engineer
• Worked on Industrial Engineering Fab Models Simulations using Applied Materials AutoSched simulator to analyze impact of AMHS design. Main tasks included developing a GUI using JBOSS to automate Fab data collection that feeds the simulator and customizing functions in the simulator using object oriented C++.
• Developed Industrial Engineering Web based reports intended for detailed data analysis and monitoring of semiconductor manufacturing Fabs. Used multiple platforms including QlikView, CGI PERL, JBOSS, Business Objects, and Oracle PL/SQL and Linux shell scripting. Installed and set up JBOSS, Apache, Hudson/Jenkins application servers. Familiar with Subversion.
Feescale Semiconductor
November 2002 - October 2009Electrical Engineer
Analyzed Fab Silicon electrical data and contributed in defining proper metrics for detecting disconnects between model and silicon. Simulated and validated spice electrical models/circuits accuracy. Implemented infrastructure of the Performance to Targets tracking for the next technology CMOS devices.
• Defined and managed Fab crucial electrical parameters and specs tracking for the 45, 65 and 90nm CMOS bulk and SOI technologies by efficient communications and collaborations with device, model and design engineers.
• Analyzed post silicon data parametric variability and enabled Monte Carlo statistical model simulations, which led to better prediction of Fab product variability and improvement in the generation of model best-case and worst case design corners.
• Contributed in improving the automation of model to silicon and model to model comparisons for the device crucial parameters using PERL programming. This effort led to speeding up the process for debugging model inaccuracies and/or silicon misbehavior