What are the responsibilities and job description for the Transformation and Innovation Team - Data Domain Modeling Associate position at JPMorgan Chase?
Information Architecture within Corporate Financial Analysis (FA) is working to build scalable, end-to-end data products that enable centralized, self-service data sourcing through an array of consumption patterns optimized for Planning and Analysis (P&A) functions.
As a Data Domain Modeler, within the Transformation & Innovation team, you will play a key role in designing and implementation of end-to-end data models starting from raw data to the semantic layer that makes our data more accessible and understandable for different persona ranging from finance users, data analysts, automation, quantitative research and machine learning teams.
Job Responsibilities:
Design, develop, test, and refine data models and analytic prototypes and work with a variety of data sets and use cases to support different Planning & Analysis processes, collaborating with senior team members on solution design
Contribute to solve complex and high visibility data challenges in finance, working at the intersection of finance and technology
Support the design and development of new cloud base data lakehouse for the P&A community, leverage by Analyst through to the CFO for daily reporting
Guide and support data consumers about how to leverage the data products for analytics, planning and calculations
Leverage and review AI-assisted coding tools (e.g. Copilot, Claude) to accelerate data design development, SQL optimization, and prototype iteration
Identify opportunism to embed AI into recurring P&A workflows by defining data contracts and interfaces that is needed to work effectively
Collaborate with other high-performing teams within JPM to inspire innovation and champion change throughout the bank
Required qualifications, capabilities, and skills:
Bachelor’s degree in computer science, data science, information systems, business analytics, or related discipline; 3 years of relevant experience in developing, testing, and refining data models and analytic prototypes using dimensional and relational data models
Strong analytical and problem solving skills with attention to details; hands on in building and prototyping data model to address user needs and support their delivery
Demonstrate experience using SQL and Python for data analysis, engineering, and transformation ; comfortable writing queries and scripts to build data pipelines, uncover business insights, and support model development
Curious and inquisitive mind to dig deep into the business and data to understand the context: open to challenge the status quo and striving for continuous improvement
Familiar with prompt engineering principles and the ability to effectively use LLM-based tools to accelerate development task such as writing SQL, generating documentation, or exploring data.
Hands on approach to creating solutions aligned to the tools and skills of the client user and experience with ETL / ELT process and architecture to move data across pipelines in a lake
Experience building models suited for interactive dashboard or cube consumption and familiarity with cloud-based data lake platforms such as AWS, Azure or Google Cloud
Preferred qualifications, capabilities, and skills:
Experience with Databricks , including notebook-based development
Experience working with headcount, workforce, or HR data domains