Data Architect



Will be responsible for Architecting/Designing/Developing MDM data management. MDM Data is a collection of Northern Parties and contains

Will also provide a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture.

Experience Level: 10+ years

Qualifications:
Knowledge and hands-on development experience implementing MDM solutions using IBM MDM Advanced/Standard Edition v11.x., v12.x
Customization of IBM Physical MDM (Extensions, Additions, Behavior extensions, Notifications, External Rules, Event Handling, Specs, Batch Processor, etc).
Strong hands-on development experience, Suspect Duplicate Processing, Survivorship Rules.
Sound understanding of IBM Physical MDM concepts, Data Model (Party/Contract) and services/transactions.
Comfortable in configuring probabilistic matching engine (PME) (i.e. strong experience in developing and tuning the algorithm), Match iteration and tuning experience.
Review current suspect matching algorithm and determine scope for improvement and implement the improvements.
Comfortable in customizing DSUI(JSF based application)
Strong in Core Java and SQL/PLSQL
Comfortable in Unix scripting and commands
Very strong customer interaction and communication skill
Should be ready to work with offshore as coordinator

Nice to Haves:

Understanding of the investment management business, multiple asset classes, client and regulatory reporting
Investment/financial technology systems within a large scale Asset Management setting

Tasks & responsibilities:

Apply data management and architecture expertise in developing solution architecture and advanced analytics solution design, including reporting technology; Articulate tradeoffs, strengths, and weaknesses of various architectures and their components to determine the best design given use cases and constraints,
Identify internal and external data sources for potential integration into platform; Lead data migration and integration projects,
Create appropriate standards and processes to ensure quality and consistency of data in the platform,
Outline best practices and establish standards for data strategy, data lifecycle, data ownership, data definition, and data classification,
Collaborate with stakeholders and advanced analytics business partners to understand business needs and to identify and define advanced analytics solutions





Originally posted on Himalayas