J.P. Morgan is a leading global financial services firm, established over 200 years ago:
o We are the leader in investment banking, financial services for consumers and small businesses, commercial banking, financial transaction processing, and asset management.
o We have assets of $2.5 trillion and operations worldwide
o We operate in more than 100 markets.
o We have more than 243,000 employees globally.
Our wholesale businesses include J.P. Morgan’s Asset Management, Commercial Banking and the Corporate & Investment Bank which provide products and services to corporations, governments, municipalities, non-profits, institutions, financial intermediaries and high-net worth individuals and families.
Our corporate functions support the entire organization and include the following functions: Accounting, Audit, Finance, Human Resources, Operations, and
J.P. Morgan in India provides a comprehensive range of Corporate & Investment Banking, Commercial Banking, Asset & Wealth Management, and Corporate functions services and solutions to our clients, executing some of the most important financial transactions and providing essential strategic advice to our clients such as the government, large domestic and multi-national corporations, non-government organizations and financial institutions and investors. India is a key market for
JPMorgan Chase globally and our employees in India are a critical part of how we do business globally and are integrated within our businesses. Our Global Service
Centers (GSCs) are strategically positioned in Mumbai, Bangalore and Hyderabad to support the firm’s operations regionally and globally. The centers provide comprehensive strategic support across technology and business operations processing to all lines of business and the corporate functions.
The Consumer Banking Specialist is responsible for providing timely resolutions to our Consumer and Community Banking customer’s queries. They will connect with our customers through inbound/outbound calls regarding transactions on their accounts such as payments, loans, charges/fees, interest rates, rewards and other issues.
Data and Analytics Data Management provides providing Data Architecture support for modeling, designing and executing solutions that enable data value for our MIS partners.
Implement data delivery solutions - data design, ETL procedures, end-to-end data process management, and administering enterprise controls
Oversee data management process - including design, documentation, maintenance, enhancements and validation
Designing Logical & Physical Data Models.
Guiding team on best practices and performance improvement.
Creating & maintaining Metadata Dictionary, Data Lineage and other process related documentation.
Programming in line with the accepted Coding Standards and Techniques.
Adhering to internal governance processes (promoting codes to higher environments, Time Tracking, usage of version control tool, and usage of JIRA).
Implementing strong control practices in the programs.
Responsible for high quality output of projects by effectively using industry accepted testing practices.
Help define processes for data architecture design review and performance optimization.
Provide production support of existing ETL processes.
Interact with multiple data sources (i.e. Oracle, Teradata, Informix, flatfiles,DB2).
Develop, document and maintain functional, technical & business test scripts and results.
5+ years of experience leading and working on MSBI tool set (especially SSIS ) and various data sources.
Very sound knowledge on designing Logical & Physical Data Models.
Very good PL/SQL coding required to transform the transactional data and load them as per business needs.
Demonstrated knowledge of ETL concepts such as data integration, enrichment, consolidation and aggregation; change, data capture and transformation; error handling. Experience in data extraction; Transforming and Loading using tools in SQL Server Integration Services.
Adapts ETL processes to accommodate changes in source systems and new business user requirements.
Familiarity with semantic layers and creating dimensional models.
Familiarity with data warehousing concepts, especially OLAP
Exposure to Big Data technologies and migrating the RDBMS datasets to Hadoop is an added advantage.