SUMMARY:

• Over 12+ years of overall experience in the IT industry in the fields of, planning and executing all phases of software life cycle starting with requirement study, analysis, design development, testing, implementation and maintenance using object oriented analysis and design Methodologies (OOAD).
• Performed the role of Senior Software Analyst, Lead, Project Manager in Medical Sector at CVS Pharmacy, MDL Information Systems, Cedar - Sinai Medical Center, St. Jude Medical Center in the streams of Drug Development, Patient Care, Pacemakers (Wifi).
• I have an internal understanding of Hadoop, HDFS, Hive (TEXTILE, SEQUENCEFILE, ORC, RCFILE Row-oriented & Column-oriented ) systems both on Stand-alone & Cloud implementations.
• I am familiar & have improvement suggestions to address the System Performance issues that implements Hadoop, Hive, HDFS architectures, since at the crust of it all depends on Virtual Machine spawning, pooling & administration; where in my experience I have suggested to reduce transactional turn around time by utilizing RAID storage systems for HDFS
• & introducing either Software/Hardware Load Balancers between server running MapReduce & server running TaskTracker. This suggestion I gave specifically since the Virtual
• Machine (JobTracker) spawning is conducted by TaskTracker via its connect pool (generally set to 4 connections), and the catch exists that considering the load on the system there does present a possibility that JobTracker Virtual Machine may introduce delay that would eventually delay entire MapReduce job, in turn drastically affecting the Performance of the entire system.
• I have suggested in my experiences workarounds in case of migrating legacy data from DBMS or RDBMS or Mainframe Databases to Hadoop, HBASE, Hive (stand-alone or cloud) implementation in the fields of Cluster Data Indexing, Data Indexing, Data Sorting before migration of data.
• I have suggested in my experiences changes to RCFile implementation from Column-oriented systems to Row-oriented systems for regularly changing data like transaction tables data to reduce the systems’ performance turn around time.
• I have analyzed, designed & implemented Products and Frameworks / Harnesses / Systems for Client-Sever, 2-Tier, 3-Tier, N-Tier, SaaS, Embedded, Medical Device, Satellite Uplink-Downlink, Mobile Devices, Cloud, App, Real Time Data Streaming based systems.
• I have experience of Agile Frameworks of Continuous Integration acting as Scrum Master & Individual Contributor too, where I have used both stick-notes & professional software (Rally, Scrumforce etc.) to manage team activities I lead.
• I have analyzed, designed & implemented RealTime Embedded Systems with Artificial Intelligence & Machine Learning Language for Luxury Travel Industries and Audio & Video Security Surveillance Industries.

TECHNICAL SKILLS;

Software Frameworks I Have Used: J2EE Java RMI Windows DotNet Cocoa Framework CGI XAP (Framework Workflow) SpeechBox Framework Speech Framework

BigData Management Systems I Have Used: MongoDB, HBase Hadoop, HDFS, MapReduce, Hive

Database Drivers & Connectors I Have Used: Native drivers JetBridge NetBridge DAO ADO ADODB ADODB.Net OLTP ODBC ODB.Net JDBC OLEDB

Software Methodologies I Have Used: Rational Unified Process (RUP) Expectation & Reality (E-R) Gap Analysis IEEE CMMI (Capability Maturity Model) Rapid Action, Development (RAD) Agile SOX QII SQA SOA OOAD SixSigma SDLC QDLC SOP98-1, DotNet Remoting Scrum Testing (Smoke Baseline Benchmark Unit Whitebox Blackbox, Greybox Load Performance Stress User Acceptance System Integration Network, Configuration & Installation CI/CD Build Regression Behavioral Programming Test Data, Driven Key Driven Real-Time Video Streaming Video Chatting Soak Litmus Alpha Beta), Test Driven Development (TDD) FDA 21CFR Part 11 Network & System Testing

Hardware Technologies I Have Used: PCB Designing MakerBot 3D Printer Weilding (MIG TIG ARC Oxy-Acetylene Torch) Tinning Archaeometallurgy Metal Rolling, Beating, Packaging Carbonyl metallurgy Chrome plating Copper Plating Casting Metal (Traditional) Forging Metal (Traditional) Bronzing Anodizing (Type I, II, III & Organic)

PROFESSIONAL EXPERIENCE:

Principal Software Engineer

Confidential, San Jose, California

Mobile Automation Architect

Confidential, Fremont, California

Mobile Automation Architect

Confidential, Pleasanton, California

Data Scientist, Programmer AngularJS, Analyst & Architect

Confidential, Fremont, California

Data Scientist, Programmer AngularJS, Analyst & Architect

Confidential

Confidential, Sunnyvale, California

Senior Software Automation Engineer, Data Scientist & Architect

Confidential

Senior Software Automation Engineer & Architect

Confidential

Senior Software Automation Engineer & Architect

Confidential, San Francisco, California

Senior Software Design Engineer & Architect

Confidential, Sunnyvale, California

Senior Software Development Engineer

Confidential, Cupertino, California

Senior Software Development Engineer in Performance Testing

Confidential, Mountain View, California

Senior Software Development Engineer in Testing

Confidential, San Ramon, California

Senior Software Development Engineer in Testing

Responsibilities:

• Performed the role of Senior Software Analyst, Lead, Project Manager in Medical Sector at CVS Pharmacy, MDL Information Systems, Cedar - Sinai Medical Center, St. Jude Medical Center in the streams of Drug Development, Patient Care, Pacemakers (Wifi).
• Performed as Senior Software Analyst, Quality Assurance Lead in Banking & Finance Sector at Countrywide Home Loans, Visa, Confidential in the streams of Home Loan Originating Systems, Credit Card Processing, Check Processing (ACH), Brazilian Payment Gateway, Federal Taxations.
• I have an internal understanding of Hadoop, HDFS, Hive (TEXTILE, SEQUENCEFILE, ORC, RCFILE Row-oriented & Column-oriented ) systems both on Stand-alone & Cloud implementations.
• I am familiar & have improvement suggestions to address the System Performance issues that implements Hadoop, Hive, HDFS architectures, since at the crust of it all depends on Virtual Machine spawning, pooling & administration; where in my experience I have suggested to reduce transactional turn around time by utilizing RAID storage systems for HDFS
• & introducing either Software/Hardware Load Balancers between server running MapReduce & server running TaskTracker. This suggestion I gave specifically since the Virtual
• Machine (JobTracker) spawning is conducted by TaskTracker via its connect pool (generally set to 4 connections), and the catch exists that considering the load on the system there does present a possibility that JobTracker Virtual Machine may introduce delay that would eventually delay entire MapReduce job, in turn drastically affecting the Performance of the entire system.
• I have suggested in my experiences workarounds in case of migrating legacy data from DBMS or RDBMS or Mainframe Databases to Hadoop, HBASE, Hive (stand-alone or cloud) implementation in the fields of Cluster Data Indexing, Data Indexing, Data Sorting before migration of data.