Consumer Card - Data Modelling and Mapping Specialist
at J.P. Morgan
Posted 19 days ago
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- Compensation
- Not specified
- City
- New York City
- Country
- United States
Currency: Not specified
The Data Modelling and Mapping Specialist will document and map data flows and attributes across systems to support Consumer Card products, ensuring clarity, governance, and integration for analytics and reporting. You will develop and maintain data models, KPIs, ETL processes, and metadata to enable product and analytics use cases while working closely with business, IT, and analytics stakeholders. The role includes identifying and mitigating data risks, supporting data governance and protection standards, and may include managing direct or matrixed staff. Experience with SQL/Python/R, data modeling tools, cloud/big data platforms, and strong understanding of data quality and governance is required.
Location: New York, NY, United States
Join a team that unifies data and analytics talent across Consumer & Community Banking to responsibly leverage data to build competitive advantages for our businesses with value and protection for customers.
As a Data Modelling and Mapping Specialist, with in the Consumer Card Team, you will use data to accelerate product development, business growth, and improve the Chase customer experience, at the same time, help us to deliver critical business initiatives.
Job Responsibilities:
- Accurately document data flows across various systems, ensuring clarity and comprehensiveness in the representation of data movement and transformation and investigate and analyze different data attributes within multiple systems to understand and document their characteristics, usage, and impact on business processes.
- Track and map the relationships between data attributes and systems, identifying dependencies and interactions to optimize data integration, while developing and maintaining data models that reflect the current and future state of data architecture, supporting business objectives and data governance.
- Design and implement key performance indicators (KPIs) to measure and evaluate progress toward key data flow goals and work closely with business analysts, IT teams, and other stakeholders to gather requirements and provide insights into data-related challenges and opportunities.
- Create plans for the development and delivery of product data to support strategic business objectives, business operations, advanced analytics, and metrics and reporting and work with key partners to drive an understanding of the data and its use within the business. Provide subject matter expertise with respect to the content and use of data in the product and associated business area.
- Identify the scope of critical data within their product, ensuring that the prioritized data is well-documented as to its meaning and purpose, and classified accordingly with metadata to enable its understanding and control and support the aligned Data & Analytics lead for their product by identifying data required to be integrated into analytics platforms to support analytics projects.
- Develop processes and procedures to identify, monitor, and mitigate data risks for data in the product, including risks related to data protection, data retention and destruction, data storage, data use, and data quality and manage the execution of tasks to comply with Firmwide policies, standards, and procedures related to the integrity and protection of data in the product.
- Manage direct or matrixed staff to execute specific data-related tasks.
Required qualifications, capabilities, and skills:
- Bachelor's degree required, with 4+ years of industry experience in a data-related field and subject matter expertise in business or product data or processes.
- Data Querying capabilities: such as SQL, Python, or R, to develop and maintain data models and mappings.
- Proficiency in data engineering techniques, including data extraction, transformation, and loading (ETL) processes, to support robust data management and integration, such as Erwin
- Technical expertise in data management, data engineering, data pipelines, data modeling, data architecture, and governance, along with proficiency in data modelling tools and techniques.
- Experience with cloud platforms like AWS, Google, or Azure, and/or big data technologies such as Hadoop, Spark, Alteryx, Snowflake.
- Strong understanding of data quality, privacy, and security standards, and experience with data governance frameworks and tools.
- Knowledge of industry best practices for data management and modelling.
Preferred qualifications, capabilities, and skills:
- Credit Card domain knowledge is a plus.
