SUMMARY

• Data Warehouse and ETL Architect with 10 plus years career experience in Architecture, Design, Development & Support of Large scale ETL projects spanning all phases of Data warehousing and software development life cycle.
• Hands on experience in coding and development.
• Very Strong SQL and ETL Skills.
• Data Modeling experience in ERWIN and Infosphere Data Architect.
• Significant experience working with multi - site teams.
• Knowledge of Amazon Red Shift, Google Big Query and Cloud Data warehouse technologies.
• Extensive experience Designing, Implementing, Testing and Managing complex large scale projects in Enterprise Data Warehouse.
• Hands on experience in project development using using ETL tools such as IBM Datastage 8.1,9.1, Database platforms IBM DB2 Z/oS, DB2 LUW, SQL Server, Oracle.
• Proven Project management skills executing various size projects within tight deadlines working with stake holders using both Agile and Waterfall methodologies.
• Experience working on Oracle, OCI Stages, DB2 Connector and API Stages.
• Created end to end data architecture for projects working with Business Analysts, Line of business, Application Architects to arrive at optimal design solutions from functional requirements.
• Identified opportunities for creating re-usable components and implemented.
• Worked with Data Analysts, Solution Architects and Vendors to translate business requirements into technical requirements and designs.
• Skilled in working across enterprise teams & global teams arrive at consensus based solutions.
• Ability to grasp project requirements issues quickly and propose resolutions plans.
• Completed several full cycle implementations of large ETL Projects in Data warehouse on Datastage, Db2 Z/OS, SQL Server, Oracle.
• Extensive performance tuning experience in ETL - Datastage and SQL - Database
• ETL performance tuning by increasing rows processed per second using Optimized job design with correct stage usage, Partitioning, Node configurations management.
• Expertise in developing datastage jobs for high volume processing and bulk load as an ETL Developer and Data warehouse Developer.
• Skilled in addressing production issues with quick understanding and resolution.
• Good experience in scheduling tool - Tivoli work scheduler (TWS).
• Lead Data Source Exploration and Integration services by evaluating business value and feasibility of new data sources and collaborating with data modelers
• Lead Datastage migration project from 8.1 to 9.1 successfully.
• Very strong advanced SQL skills on multiple database platforms and extensive experience implementing complex looping logic, recursive CTE, Explain plan analysis and performance optimization.
• Expertise in SQL Scripting, writing stored procedures, triggers and complex CTE across variety of databases.
• Specialized in performance tuning SQL and Database configuration using concepts such as explain plan, index analysis, lock dependencies, profiler, table variable usage.
• Experienced in IBM DB2 Analytics Accelerato r for z/OS ( IDAA ) using IBM Netezza for Big data.
• Strong data administration skills such as locking, partitioning, query optimization, indexes, Access path analysis.
• Experience working with IBM on PMR's configuring Bulk load, Netezza.
• Certified in Big Data and Hadoop from IBM Big Data University.
• In-depth knowledge in principles of Data warehousing using Fact Tables, Dimensions Tables, Star and snow flake schema modeling, ODS, OLAP, Conformed Dimensions.
• Designed logical conceptual and physical data models from ground up for projects and lead the database design.
• Experienced in designing solutions for OLTP, OLAP systems for performance.
• Working experience on BI reporting tools Tableau, Qlik view.
• Hands on NoSQL experience .
• Well experienced working in onshore-offshore development model.
• Proficient in Data Analysis and Business Intelligence Analysis using Logical and Physical models.
• Working knowledge on Mainframe.
• Extensive Data modeling experience in ERWIN and Infosphere Data Architect tool building relational and dimensional models - conceptual, logical and physical data models.
• Created data models from ground up for 'Deposit simplification', 'Small business banking' projects.
• Extensive SQL and Database development experience and data model normalization.
• Created best practices for Data Governance.
• Designed and developed the architecture, road map, and standards for the Enterprise Data warehouse.
• Established guidelines for Data warehouse, ETL, Data model and Database development.
• Took initiatives for new strategic projects and suggested to management for implementing such as SLA Report.
• Skilled in understanding difficult concepts/ problems and state in a format meaningful to colleagues and management.
• Acted as the go to person for technical assistance and guidance within the team and external teams.
• Involved in recruitment process, selecting EDW leads who align with organization requirements.
• Created process for on-boarding new team members and help them come up to speed in team.
• Nurtured, provided guidance for my team for career growth and team building.
• Technical lead for the project working with developers at offshore, ensuring smooth collaboration .
• Experience working with and managing both small and large project teams.
• Led successful implementation of projects interfacing with cross functional teams building consensus and driving towards practical solutions.
• Planned and worked on implementing the road maps for enterprise projects.
• Created detailed step wise deployment plans for large enterprise projects.
• Reviewed development code and artifacts.

TECHNICAL SKILLS

• IBM Websphere Datastage 7.X
• 8.1
• 9.1
• Manager
• Designer
• Director
• SSISERWIN
• Infosphere Data Architect
• Microsoft VisioCrystal Reports - Business objects
• Tableau. QlikviewMongo DB
• Amazon Redshift AwS. Google Big Query
• NetezzaMicrosoft SQL Server 2000/2005/2016
• IBM DB2 Z/OS
• DB2 LUW
• Oracle 10g/9iSkilled in Hive
• Map Reduce
• Hadoop
• Non-relational storage system (NoSQL)
• IBM DB2 Analytics Accelerator for z/OS
• IBM Data Studio Unix shell scripting
• Korn shell
• Python IBM Tivoli Workload Scheduler (TWS)C
• C++
• Java and SQLUnix
• AIX
• Windows
• Linux and Mainframe.

PROFESSIONAL EXPERIENCE

Confidential

Architect & Technical Lead

Responsibilities:

• Responsible for design, architecture and execution of several Federal compliance requirements to create and maintain Data Mart.
• Created end to end Architecture for the projects (listed in following page) covering ETL and database design.
• Published data road map for many of the organizations high impact IT projects.
• Technical consultant to Business analysts, stakeholders and internal management on projects.
• Enhanced the enterprise BI data architecture to increase the robustness, performance, and scalability of systems.
• Involved in data governance, data administration, data integration and data modeling.
• Designed the dimensional data model and data mart for the projects using ERWIN .
• Provided technical expertise and direction for solutions to new project design requirements,
• Wide range of factors such as Volumetrics, Grain, Data growth were analyzed and data architecture and model was designed accordingly. Result - The architecture and model had the allowance for future requirements leading to very few modifications long term thereby reducing rework and cost associated.
• Responsible for mentoring onshore tech leads and global teams.
• Created and ensured compliance to standards for ETL and Database design, coding and implementation plan.
• Implemented features such as re-start ability, re-usable components, partition management and override options.
• Made analysis on performance of the EDW system periodically and provided recommendations on architecture and code improvement.
• Performance tuning of large volume (multi million) processing jobs ; Historical data changes tracking /Slowly changing dimension.
• Implemented migration from Datastage 8.X to 9.X for Data warehouse system.
• Performed root cause analysis/ trouble shooting Data stage and Database issues.
• Analyze data issue using advanced SQL queries across wide subject areas.
• Implemented Bulk batch high volume processing in Datastage using Bulk Load features.
• Implemented jobs to process ETL control table data for audit, Job object search and analysis,
• Read and write Mainframe Files from datastage.
• Extensively used various ETL stages like Folder stage, Change capture, Merge, Transformer, DB2 Connector, API, Join, FTP Stage, Stored procedure stage, XML, Copy, Modify, Row generator, surrogate key generator, Remove duplicate etc. File manipulation, validation, archival logic, notification handling logic were implemented using shell script.
• Won customer appreciation from several Senior management members of the company.
• As part of this project, the Data warehouse Design involved consolidating data received from multiple source systems within the bank, apply validation and cleansing rules.
• Liquidity ratio calculated at daily and monthly intervals using multi system data.
• Special jobs created to partition and manage the data into 100 partitions for history keeping purpose using combination of ETL and SQL.
• Additional special jobs created to manage data with similar partitions for Daily data.

Senior Data Analyst

Confidential

Responsibilities:

• Lead and Data modeler for multiple banking projects.
• Responsible for the Data Analytics design and data modeling.
• Worked with solution architects and business analysts to convert business requirements to SQL Design.
• Functionally many complex scenarios discussed and solutions arrived at, followed by technical implementation.
• Provided high performance solutions by optimizing Database by tuning SQL code, locking mechanisms, global temporary table usage and indexes.
• Won customer appreciation on successful project delivery.

SQL Lead Developer

Confidential

Responsibilities:

• Responsible for creating solutions in SQL according to business requirements.
• Created stored procedures and complex queries according to specific needs for analysis.
• Achieved high performance metrics in SQL owing to optimization concepts employed such as table variable, index tuning, execution plan analysis and correction.