Engage with finance, tech, client org, and data engineering teams to gather requirements, understand application processing, identify gaps and align build models for business needs.
Key Responsibilities:
- Develop good understanding of various metrics used in calculations and reporting of Return on Tangible Common Equity (RoTCE)
- Apply a methodological approach to decompose calculation methods used for various metrics in RoTCE
- Ensure a clear central definition of each metric and how it is used across various lenses, including business unit, products, geography time periods.
- Lead assessment of end-to-end data flows for all data elements used in a particular metrics, including coordinating with the business in identifying critical data, defining standards and quality expectations, and prioritize remediation of data issues.
- Establish an inventory of data elements required to perform Client RoTCE calculations, allocations and reporting
- Produce a gap assessment of the current vs. strategic sourcing
- Identify appropriate strategic source for critical data elements used in calculation & reporting of RoTCE
- Build conceptual and logical data models for all metrics used in RoTCE
- Create a matrix of tactical vs strategic CSIs and frequency of data availability
- Implementation of stringent data quality rules to ensure accuracy, completeness and consistency of the financial data.
- Draft detailed specification containing calculations, data transformations and aggregation logic for each metric used in Client RoTCE to tech teams
Skills & Qualification
- 10+ years of combined experience in banking and financial services industry, information technology and/or data controls and governance.
- Preferably Engineering Graduate with Post Graduation in Finance
- Extensive experience in the capital markets business and processes
- Deep understanding of different products (i.e., derivatives, FX, securities trading and securities financing)
- Sound knowledge about Accounting, Risk Management Concepts
- Experience with data management processes and tools and applications, including process mapping and lineage toolsets.
- Strong knowledge of structured/unstructured databases, data modeling, data management, rapid / iterative development methodologies and data governance tools.
- Strong understanding of data governance issues, policies, regulatory requirements, and industry information affecting the business environment.
- Demonstrated stakeholder management skills.
- Actively managed various aspects of data initiatives including analysis, planning, execution, and day-to-day production management.
- Technical Skills / Knowledge – Understand schema / models, can explain difference between conceptual, logical, physical models, relational models, understands inheritance concepts for models and has understanding of SDLC process
- Technology / Program experience – Open API specifications (Swagger), JSON schema, Tools: VSstudio, GitHub, lightspeed
- Soft Skills – Analytical thinking – ability to break down complex data structures and processes to identify issues and develop logical models that meet business needs.
- Communication skills – needs to be able to communicate with technical and non-technical stakeholders to gather requirement, express needs and develop clear documentation
- Languages Required – English
- Excellent presentation skills, business and technical writing, and verbal communication skills to support decision-making and actions
- Excellent problem-solving and critical thinking skills to recognize and comprehend complex data flow and designs.
- Self-motivated and able to dynamically determine priorities
- Experience with big data technologies: Hadoop, spark or snowflake
- Data visualization skills – can help in creating visual representation of data models and provide input to UX / UI team to help make it easier to communicate complex model relationships with stakeholders
Applications Development
Time Type:
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