SUMMARY:

• I am a Hortonworks certified Hadoop Developer with 20+ years of Data Architect experience, based out of Dallas, TX with consulting expertise spread across multiple clients, continents and technologies.
• Primarily on large scale data integration projects for Confidential 500 companies and Federal government working with the Big4 consulting firms.
• I have been responsible for delivering multiple projects from beginning to end of different types like Big Data Proof of Concepts, Master Data Management, Data Warehousing and Business Intelligence, Data Migration (system upgrades or mergers and acquisitions), Regulatory compliance and Fraud prevention
• My expertise is in building corporate level highly efficient, manageable and measureable Data Transformation Processes with structured and un - structured data using Pig, Hive, MapReduce, Python, “R”, ETL Tools like Informatica PowerCenter, PowerExchange and Confidential InfoSphere Suite (DataStage and QualityStage) producing more accurate and informative results for the organization and enhancing it's data quality by record linkage, identity resolution, data matching, loading and maintaining security while providing frequent data quality reports to continually monitor and improve standards overtime

PRODUCTS & TECHNOLOGIES:

Big Data/Hadoop Eco system: Confidential, Hadoop, YARN, MapReduce, MongoDB, Hive, Pig, Sqoop, Flume, “R” and Python

ETL Tools & Other: InfoSphere DataStage/QualityStage, Informatica, PowerCenter, PowerExchange, PowerMart, Erwin, Eclipse

RDBMS: Oracle, DB2 UDB, Sybase, Netezza, Teradata, MySql, SQLServer, Adaptive Server Anywhere, iAnywhere

ERP / CRM: SAP-ABAP, Siebel-EIM, Peoplesoft

Languages/ Scripting: Java, Python, XML, JSON, awk, shell, PAL, CICS, Cobol, JCL, SQL, PL/SQL

Mainframe: MVS, JCL, CICS, Cobol, PL/I, VSAM, DB2

Middleware: MQSeries, TIBCO

Operating Systems: AIX, SUN, HP-UX, LINUX, Windows

Project Management: Agile, SDLC, Waterfall

Other: System Design and Documentation, Disaster / Capacity planning, Statistical modeling, regression analysis, classification, correlation, predictive modeling

PROFESSIONAL EXPERIENCE:

Confidential

Data Architect

Environment: Informatica PowerCenter, PowerExchange, Hadoop, Java, Confidential, YARN, Hive, Sqoop, Oozie, “R”, Oracle

Responsibilities:

• Real time data replication into Confidential data lake from multiple applications and smart meters pushing meter readings every 15 minutes from 3.2 million meters to be used by data scientists to develop predictive models for forecasting and fraud analysis
• Built ETL processes to support spinning-up of environment for application development, testing and continuous deployment of applications through puppet and automic with different data slices that could be picked up and used in creation of the environments
• Prototyped usage of MongoDB for storage of customer support tickets in a NoSQL data base

Confidential

Application Architect / Big Data Trainer

Environment: Python, “R”, Hadoop, Java, Confidential, MapReduce/YARN, Hive, Sqoop and Oozie

Responsibilities:

• Design and develop API’s and web services call to score individuals fraud probability based on feeds from city open data initiative, Office of Foreign Asset Control ( Confidential ) and an exhaustive list of disparate sources that is linked together with proprietary matching algorithm using “R” to detect and predict fraud and generate notification based on aggregated thresholds
• Classroom training for Big Data foundation courses teaching Hadoop essentials ( Confidential, MapReduce, YARN, Hive, Sqoop and Oozie)

Confidential, Charleston WV

Architect and Developer

Environment: AWS, Hadoop, Confidential, Java, Regex, MapReduce, Hive, Sqoop and Oozie

Responsibilities:

• Created a Big Data proof of concept using Hadoop ecosystem to profile all existing 800 thousand items in the item master and remove duplication and standardize data to improve quality that has been deteriorating over time as the client has been acquiring data for almost a century and growing exponentially with mergers and acquisition.
• Without impacting the existing environment, we could setup an AWS cluster in a very short time with Confidential setup, the process involved downloading the existing item master data from the existing Legacy systems into files uploaded into the Amazon S3 environment Java regular expressions where extensively used in the initial steps to perform multiple rounds of data analysis on the standardized free form description fields and use these fields as MapReduce keys using which we were able to create multiple correlation algorithm and provide the results to SME’s who could then go back into the legacy systems and apply the corrections

Confidential, Charleston, WV

DataQuality Consultant

Environment: WebSphere DataStage/QualityStage, ProfileStage, DB2, PAL

Responsibilities:

• Overtime the data quality in the existing system has been deteriorating due to systems currently allowing users to enter data into free form fields instead of leveraging controls such as drop down list constraints and numerous acquisitions and mergers
• In it’s attempt to implement an MDM tool MRC is trying to cleanse the existing 800K product records before loading into the new system with minimal impact to business and SME’s

Confidential, Dallas TX

Development Manager

Environment: WebSphere DataStage/QualityStage, InfoAnalyzer, Oracle

Responsibilities:

• Leading the Confidential BIS resolution groups InfoSphere Development effort in conversion of the existing SQL Server update scripts into Confidential Infosphere toolkit using out of the box features/rule sets for data cleansing and standardization building new pattern files and DataStage logic to process free form data and compliance to the newly formulated final rule for deposit data.
• This included training all 200 download specialists in operation of the product which required development of the front end mapping using Parallel Extender jobs for every new bank to be mapped to the standard final rule layout.
• Designed and Developed an application to manage and track the property maintenance details of defaulted properties acquired by resolution of financial institutions all over the country to facilitate marketing of these properties and providing options of ad-hoc load of property managers data upload with notification to appropriate divisions for reporting

Confidential, Arlington, VA

ETL Architect

Environment: DataStage 7.5, QualityStage 7.5, Oracle 10g, PegaSystems

Responsibilities:

• Returned to Confidential to assist Confidential in implementing new requirements into the existing system one of the major change being implementation of Claims Association Grouping to identify groups of accounts that might result in over-insurance based on PII information and account details generating meaningful groups that could be reported on.
• Also implemented the final NPR which impacted the whole CAS system

Confidential, Bentonville, AR

ETL Architect

Environment: Websphere 8, DataStage, QualityStage, DB2, Teradata, Informix, AIX, SAP, Confidential

Responsibilities:

• Due to the difficulty of customizing the home grown systems for each market Confidential is moving some of it’s IT operations into SAP ERP solutions and is using Confidential ’s Websphere Suite and Confidential for data cleansing, normalization, transformation, enrichment and loading into SAP and data remediation in the existing legacy systems.
• The end objective being reduced inventory levels, improved customer in-stock predictability, and overall profitability

Confidential, Arlington, VA

ETL Architect

Environment: DataStage 7.5, QualityStage 7.5, Oracle 10g, PegaSystems

Responsibilities:

• Also assisted in the data analysis of few large banks in the United States with a customer base of more than 2.5 million account for Advanced Notice of Proposed Rulemaking ( Confidential ) by assisting statisticians in building algorithms and datasets for analysis and predictive modeling, setting up guidelines for the required documentation and suggesting file layout and transfer methodology to be implemented by all insured financial institutions later this became the Large Bank Modernization Project