Job Description:
Finance Chief Data Office (FCDO) is setting and executing the data strategies across finance. The Data Architecture group of the FCDO team is establishing data architecture across all areas of finance, working with the operational systems, data consumers, enterprise architects, data strategy and Digital groups to roll out the data model and hydrate the data model for all consumers, including accounting, regulatory and financial reporting, CFO teams and corporate treasury. We aim to provide transparency of our data asset and actively manage the asset to contribute to the fulfilment of regulatory requirements and provide operational efficiency. The Data Architect function plays a critical role in the transformation of the organization by connecting data, technology, processes and controls.

Data Architect sets the architectural direction, gathering and analyzing business requirements, developing the appropriate data model, and provide guidance and support on data strategy. This position will play a key role in the finance digital transformation initiative.

Data Architect is expected to work with all data consumed by finance and support the organization to streamline and simplify the data pipeline, curate the data model and the data in finance:

Work closely with enterprise architects, controllers, regulatory reporting, corporate treasury, technology partners, data stewards, data strategy, and data operations to curate the finance data architecture
Assist in defining data modeling standards, and foundational best practices
Define and build the Finance Data Model for all products and services across all lines of business
Curate a single, agreed set of business terms used across Finance
Curate a single, agreed set of definitions for the business terms used across Finance
Curate a single, agreed set of harmonized values for the business terms used across Finance
Develop the operating model for maintaining the Finance Data Model. Automate repeatable process for maintaining the Finance Data model
Maintain the inventory of all data consumed by finance
Document Finance Data Lake (FDL) ’s use cases, requirements, and enhancement requests, including non-functional needs for an operating model, e.g. the need for a service, not just a tool
Document the scope (source systems/ data classes) that must be onboarded to the data lineage for the FDL
Consult, facilitate understanding and translate data requirements into logical, physical and semantic layer models across the analytical data environment
Ensure data structures are designed for flexibility to support future business needs
Ensure that data designs follow architectural best practices and appropriate business rules
Be an advocate for best practices while balancing business value and reasonable practicality
Profile and analyze source system data to determine data relationships, design constructs, consistency and quality.
Provide quality assurance (QA) test cases for use by the Data Lineage team to independently conduct quality control testing for the onboardings
Perform user acceptance testing (UAT) for the onboardings, provide feedback, and re-test until user acceptance is completed
Maintain Issue Inventory, deliverable/reporting inventory, data transformation inventory, and other identified data assets.
Enable and guide analytics user community in the understanding, location and selection of appropriate data sources to achieve key business goals
Analyze and evaluate data definition and modeling environment providing key recommendations for improvement.
Identify data gaps and process improvement opportunities, and provide recommendations for improvements incorporating best practices
Facilitate understanding of high-quality data management discipline throughout the corporation
Advocate and drive adoption of “best practices” to ensure standardization of business architecture outputs across Finance
Solid functional and business knowledge on Corporate Finance, Regulatory Reporting and Corporate Treasury business process and data model
SME knowledge of internal and external reporting (ALM/LCR/NSF), especially around data consumption requirements
Clearly define data requirements in the business context. This includes data sourcing requirements and data quality business rules.
Construct workflow charts and diagrams; studying system capabilities; writing business requirement.
Bachelor's degree in finance, accounting, or business or the equivalent combination of education and experience.5-7 years of total work experience preferred,, experience in financial planning and analysis preferred. BNY Mellon is an Equal Employment Opportunity/Affirmative Action Employer. Minorities/Females/Individuals with Disabilities/Protected Veterans. Our ambition is to build the best global team – one that is representative and inclusive of the diverse talent, clients and communities we work with and serve – and to empower our team to do their best work. We support wellbeing and a balanced life, and offer a range of family-friendly, inclusive employment policies and employee forums.

Reference : Specialist, Data modelling and Architecture jobs

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