Summary

Lead Enterprise Data BI Architect with 10 years' experience in successful management and delivery of Business Intelligence projects. Skilled communicator and visionary to build effective/productive relationships with business partners. Board experience across application and business intelligence architecture to deliver holistic, complete, modern, and integrated framework using proven methodologies and best practices.

TECHNICAL SKILLS

• Operating Systems: Experienced in Windows 95/98/2000/2003/XP/ME, DOS, Red Hat - Linux, UNIX, AMI
• Programming: Hive, Stored Procedures, JavaScript, HTML, C/C Programming, Visual Basic 6.0, SQL PL/SQL ANSI 99 Standard,, Shell Scripting
• Software: SQL Integration, Reporting and Analysis Services, Visual Studio, IIS, Data Integrator, Sharepoint, ActiveBatch Enterprise Scheduler v9, MS Office
• Databases: SQL Server 2000-2014 SQL Server DBA, MS Access, MySQL , Oracle, PostGres 9.3.
• Tools: Erwin Database Modeler, ER Studio, TFS Version Control , Attachmate, TOAD, IT Project Management, MS Query, CVS, Aqua, Sqoop.
• Ecosystems: Microsoft BI stack, Microsoft Azure Stack. HDInsight, Microsoft APS. Horton Works Data Platform.

SUMMARY OF QUALIFICATIONS

• Successfully implemented from ground up Multi-tenant enterprise data warehouse. End-to-end implementation of Data Warehouse Kimball based for Enterprise covering the complete SDLC from Requirement Gathering through closure
• Lead Data Architect for Big Data analysis on Horton Works Data platform within the Business Intelligence center of excellence team
• Data Architect responsible for Enterprise Data Warehouse design, maintenance, and continued breath of vision and emerging technologies
• Lead team of 12-15 ETL, Reporting, and Hadoop Hive/Pig/Mongo/Dynamo developers and modelers to support enterprise data warehouse.
• Enterprise BI strategy roadmap help business to create BI strategy and roadmap for enterprise data warehouse initiatives and align those with other BI solutions.
• Enterprise Data Strategy creation of Data Lake Scale Out / Big Data Eco-system HDFS Columnar Databases / MPP Appliances.
• Enterprise BI tools selection committee recommended, participated and involved in proof of concepts for Master Data Management in Microsoft SQL MDS, enterprise scheduler Active Batch and other BI initiatives for BI documenter, ER studio
• Microsoft Azure Ecosystem Center of excellence evaluation of SQL Azure, MS Azure Data Factory HDInsight.
• Dimensional Modeling - Performed Data analysis, dimension modeling Star / Snowflake and created business data model for various projects
• ETL Architecture Framework - Design and developed ETL packages using SSIS to integrate transactional data.
• Enabling Self Service BI Capabilities - PPS, SSRS, Power Pivot ,Power view based Dashboards

PROFESSIONAL EXPERIENCE

Lead Enterprise Data Architect

Confidential

• Enterprise Data Platform project is a stepping stone towards the implementation scale out architecture the formation of the big data eco-system, technology stack in the enterprise.
• Enable a data driven culture by providing near real time access to trusted data for enhanced decision making
• Implement advanced analytics and data management capabilities to gain better insights and drive consistency
• Increase the ability to respond with speed and agility to changing business conditions
• Current State Pain Points Analysis revealed the following
• Data Governance: Limited to no enterprise-wide governance in the current environments
• Deep Analytics: 80 of all analysis is ad hoc, requiring continual data gathering, queries, reconciling, etc. reducing our ability to respond quickly and with deep insights
• Performance: Current ad hoc environment suffers from poor performance resulting in extended wait times and slow response times
• Quality: Reconciling conflicting data from: 1 Multiple copies of the same data across the entire enterprise 2 No single trusted source for data 3 Thousands of data replication processes 4 Difficult to access data across data domains
• Speed: Most data ingestion processes are batch driven with limited access to real-time/near real-time data
• Trusted Source: Limited confidence in trusted data sources driving teams to recreate data sets to provide confidence in reporting limited alignment across organizations

Target State System Capabilities:

• Agility :

Ability to query across data sources

Provision and discovery

Automation

• Speed:

Faster access to data

Performance

Decreased delivery turnaround

• Self-Service:

Ability to provision data

Ability to self-source data

Information Availability in Format Desired

• Quality:

Confidential

BI Architect

JEDI is a Data Warehouse application provides integrated data storage which sources Docomo enrollment CSVs and line-of-business application such as Intelli-Japan and Axapta. Users in Risk, Sales, CC and TLC department of Asurion Japan K.K. use Microsoft Excel 2007 to access JEDI and create various kinds of analytic reports throughout their business hours. Finance Insurance Invoice and Insurance Invoice reports are developed using SSRS and deployed on reporting server.