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Business Analysis (Technology Management)

7.00 to 13.00 Years   Bangalore   12 May, 2022
Job LocationBangalore
EducationNot Mentioned
SalaryNot Disclosed
IndustryBanking / Financial Services
Functional AreaGeneral / Other SoftwareSales / BD
EmploymentTypeFull-time

Job Description

    *Institutional Technology team in Morgan Stanley is looking for experienced Data Engineer with excellent knowledge of database and python , for its Data Governance and Data Quality(DQ) platform. The candidate will be working on design and development of our next generation Data warehouse for its state of the art Data Quality and Metadata Management platform. This data warehouse should be able to store DQ Exceptions generated by diverse upstream applications in different formats in most optimal way, and then downstream applications should be able to extract these violations through RESTful services efficiently. The Candidate will be part of the team which is exploring several databases for this new warehouse like Greenplum, MongoDB and Snowflake.This will also include changing ETL layer to load data and integrate various components of end to end solution. The candidate will work with BI reporting area to generate various dashboards and other core team members for DQ rule design and execution. The platform is currently used across many systems across the breadth of Morgan Stanley in Institutional Securities, Firm Risk, Finance, Compliance and Operations Technology.- Candidate should be strong in either Qlikview/Tableau or both.- Readiness to learn either of these tools, to support existing Qlikview dashboards and build new tableau Dashboards- Good knowledge of Database/SQL concepts. Should be capable of writing SQLs/Procedures.- Ability to work on multiple projects simultaneously, Bachelors or Masters Degree with 7-10 years of relevant experience.

Keyskills :
multiple projects simultaneouslydata qualitydata governancemetadata managementetlartriskpythondesignfinancetableauwritingmongodbqlikviewdatabaseupstreammetadatareportinggreenplum

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