jpmorgan-chase-%26-co. - Mumbai, Maharashtra, India | 2024-09-11 11:51:31

Are you looking for an exciting opportunity to join a dynamic and growing team in a fast paced and challenging area? This is a unique opportunity for you to work in the Metadata Management team to partner with the Business.

AWM Chief Data Office (CDO) drives the Line-of-Business (LOB) data strategy and vision to have a scalable, agile, well-engineered data platform that powers near-real-time insights, to deliver differentiated experiences for our broad and diversified client base.

You will join the Data Product Metadata Management team within AWM CDO. The team is collectively responsible for owning, developing and maintaining the AWM LOB Core Logical Data Model and the AWM Business Glossary in support of developing data products for maintaining and accessing core enterprise level data. Our team members work closely with Senior Management to help execute the firmwide data product-based approach to accelerate data value realization with descriptive and predictive analytics in AWM. The centralized team has members in New York City, London, Mumbai, and Bangalore. 

Job Responsibilities:

• Logical data modelling. Understanding, analyzing, capturing and maintaining business data requirements using data models. Ensuring these models are consistent and that the Business Glossary is linked and maintained in a manner that allows impact assessment and lineage of metadata.
• Presentation of logical models to Data Owners/Sponsors/Concerned teams.
• Maintaining business data requirements in specific, normalized and extensible logical data models.
• Data model review and adoption. Review, adopt and integrate data models from Firmwide, other LOB and development teams into AWM LOB models. Provide review feedback to Firmwide and application teams.
• Lead/Guide/Support internal team members in producing logical data models.
• Documentation. A central data portal that details all the AWM data modelling standards. Keeping this information up to date and relevant is key. 
• Managing the linkage between the logical data model, business glossary and any physical artifacts to ensure traceability and consistency of terms and definitions.
• Loading and versioning of the models into a central Metadata repository.
• Assist Data Product owners and development teams to adopt and reuse AWM Core Logical Data Model in producing application logical models and data offering models. 
• Assist development teams to map their data implementations to the logical data model for documentation, lineage to business glossary and application model creation. 
• Maintain data integrity rules. At AWM we define the bulk of the data validation rules in the data models. Assisting data analysts with capturing business rules and translating into clear requirement specifications and then into the data model expressed in a structured language is a task the data modeler is responsible for.

Required qualifications, capabilities and skills:

• At least 5 years of data modelling experience with much of that involving conceptual, logical, canonical or semantic modelling. Knowledge of data model design patterns.
• At least 3-5 years of experience within the Financial Services industry.
• A good understanding of at least some of the following financial and business data areas:  instrument data, instrument pricing data, party & account data, positions & transactions, fund data, investment performance data, index & benchmark data, market vendor data for buy-side researchers and portfolio managers.
• Business Analysis/Requirements Gathering experience within banking and financial services industry, preferably in the Asset and Wealth Management space.
• Solid understanding/experience with a data modelling tool such as PowerDesigner, Erwin or MagicDraw, including awareness of the Metadata that underpins the tool.
• Data modelling to a level of competence sufficient to enable the coaching of others in business requirements capture.
• Experience in Metadata management, Metadata Repository, Data dictionary usage and associated tools.
• A good understanding of different modelling notations (ER, UML, ORM, etc.) and data schemas (JSON, XSD, XML).
• Strong experience in leading/directing/mentoring/training more junior members of the team.
• Good understanding of Technology concepts, practices and tools (Agile, GIT, DOS, Shell, Unix/Linux, SQL, Jira, Sharepoint, Confluence).
• An understanding of what constitutes best practice data governance and data quality controls.
• A basic understanding of database and associated technologies/tools/patterns (Relational, ETL, Star Schema)
• Working knowledge of scripting tools/technologies such as Alteryx, Python, VB script etc.

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