Business and Data Model Analyst

JP Morgan

Location: County Dublin

Job Type: Full time

Last updated

The most difficult thing is the decision to act, the rest is merely tenacity.
- Amelia Earhart

As a Model Analyst you will be part of a strategic program to onboard multiple systems, spanning different products across the Securities Services line of business, onto a single strategic data platform.

In this role, you will be responsible for collaborating with Data Dictionary owners to interrogate their data to understand and model how they represent various products and asset types, including trades, corporate action transactions, cash movements, positions / balances, ETF’s, securities lending, collateral, middle-office, custody and fund accounting, and related trading services.

A key part of your role will be to perform data analysis, data modeling and data quality analysis, including but not limited to:

  • Normalizing multiple views of data into a single model.
  • Extending/reviewing conceptual, logical, physical and metadata models.
  • Working with key stake holders to get sign-off on model design.
  • Identification of data anomalies, outliers, and data quality issues.
  • Working with Industry Standards such as Swift.
  • Trace data lineage of attributes across catalogs/dictionaries/models/physical tables/API data sets.
  • Construction/maintenance of business rules. Assisting data analysts with capturing business rules and translating those rules into clear requirements for metadata or rules developer.

It is essential to have a good working knowledge on data principles/standards, data quality, data architecture and design, and metadata management. You will have a good understanding of reference data management methods, agile methodology and will have a good working knowledge of SQL, Excel, JIRA, SharePoint, Confluence.

To be successful in this role, in addition to the above skills, you will also need to be highly collaborative, a clear and concise communicator both verbally and in writing, can deal with a vast amount of detail and be able to distill complex information in a consumable form for a wider audience.

While not mandatory, domain knowledge in financial services such as post-trade processing will be highly beneficial. Similarly, previous working experience in data warehousing programs will also be viewed favorably.

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