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Software Engineer at Google
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Experienced Lead Application Developer and Backend Engineer with a demonstrated history of working in the IOT industry. Skilled in Databases, Management, Application-Specific Integrated Circuits (ASIC), Android Development, and Embedded C. Strong engineering professional with a Master of Science (M.S.) focused in Embedded Electrical s and Computer Systems from SFSU.
San Francisco State University
Master of Science (M.S.), Embedded Electrical s and Computer Systems
January 1, 2013 – January 1, 2014
Sapthagiri
Bachelor of Engineering (BE), Electrical and Electronics Engineering
January 1, 2006 – January 1, 2010
Sheshadripuram PU College
Pr University, PCMC
January 1, 2004 – January 1, 2006
St Lourdes English school
SCHOOLING
January 1, 1994 – January 1, 2004
Software Engineer
November 1, 2019 – Present
Sunnyvale
Oracle
Software Developer / Automation Test Engineer
April 1, 2018 – September 1, 2019
Redwood City, California
Velo Labs
Application Developer and Backend Engineer
June 1, 2015 – February 1, 2018
Velo Labs
Backend Engineer at Velo Labs
May 1, 2015 – February 1, 2018
San Francisco State University
Graduate Assistant
February 1, 2013 – May 1, 2014
Tesco HSC
Software Engineer
September 1, 2010 – January 1, 2013
Carbon Mono-oxide Monitoring on Mobile Device.
January 1, 2014 – Present
Skills and Tools: C, Arduino, Java, Android. The cell phone-as-sensor approach weaves together two valuable approaches to data gathering. Wireless sensor networks consisting of hundreds or thousands of individual nodes have emerged as a new kind of instrument, capable of gathering great amounts of data that can then be aggregated and analyzed. The ability to identify where in the world a bit of data was found is the basis of geographic information systems, extremely useful tools for collecting, organizing, mapping, and understanding data within the context of location. When we can visualize data with fine granularity in a spatial context, oftentimes we can clearly pinpoint problem areas and suggest good solutions A combination of cell phone/CO detector could enable environmental scientists to monitor and track pollution across densely populated urban centers. The phones will allow scientists to gather similar kinds of geospatial data without the expense of typical GIS development and maintenance.
Transistor Aging effects due to NBTI
January 1, 2014 – May 1, 2014
Investigate the impact of aging effects on transistors, how can they be modeled and on which parameters do they depend. Furthermore, quantify the degradation of the properties of standard cells caused by aging effects. At final stage there was stimulation tests conducted for analysis to determine the timing degradation of ICs on gate-level.
Design of Full Search motion Estimator
August 1, 2013 – December 1, 2013
In this project, we designed a Motion Estimator for 48x48 search frame with 16x16 reference frame. Analysis was done on each pixel of considered block of the image with the motion estimator with their respective waveforms exhibiting its characteristics.
Automated parking lot
February 1, 2013 – May 1, 2013
Skills and tools: Python, Raspberry Pi, Ultrasonic sensors This project visions contributing a Low cost Embedded system which identifies all the empty parking slot available in the parking lot, find the nearest empty parking slot available from the point of entry and displays it at the parking lot entrance itself. This system converts the parking lot smart and user friendly.
32*64 cells memory design using SRAM
January 1, 2013 – May 1, 2013
Skills and Tools: Verilog, hspice Every digital system uses memory to store information. Semiconductor memory arrays are capable of storing large quantities of digital information which is required by digital systems. Static Random Access Memory (SRAM) is widely used in processor cache for data storage. The goal of the project was to build a fast, compact, reliable and low power consuming memory architecture. SRAM was built in different stages like SRAM array, Row Decoder, Sense Amplifier, Controller, Precharge, write driver circuits and later integrated to build 64x32 SRAM.
Development of Surge Testing on Drives
January 1, 2009 – Present
Development of Surge Testing on Drives For Testing the insulation of Household and similar low voltage electrical appliances implies the use of low voltage impulse generator providing various waveforms and energies. Impulse voltages are required in HV tests to simulate the stresses due to external and internal over voltages, and also for fundamental investigations of the breakdown mechanisms. For this purpose a repetitive impulse voltage generator with time period of 1.2/50μs is used. Our project was to generate a low voltage repetitive surge generator with a time period of 1.2/50μs with a voltage level of 500V
Cultural Fit Analysis
The candidate's experience is heavily skewed towards Software Engineering, Backend Development, and Database Administration, with a strong emphasis on Python and SQL. While there's a broad technical background, the target role is 'Data Analyst'. The projects and professional experience do not directly align with core data analysis responsibilities such as statistical modeling, advanced data visualization, machine learning for insights, or specific data analysis tools (e.g., R, advanced Excel, Tableau, Power BI, specialized Python libraries for data science like Pandas, NumPy, Scikit-learn). This indicates a significant gap in direct cultural fit for a dedicated Data Analyst role, despite strong technical skills in related areas.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on diverse technical challenges, from embedded systems to web application development and database management. Experience at Google and Oracle suggests an ability to operate within large, structured environments. The descriptions also imply problem-solving skills and a focus on improving user experience and operational efficiency.