Data Product Lead, Multi-Asset Solutions

JPMorgan Chase; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

JPMorgan Chase seeks a Data Strategy Lead for the Multi-Asset Solutions group in New York. You will partner with research and portfolio management teams to shape data products, dashboards, and decision-support tools, coordinating with data owners and technology partners to deliver fit-for-purpose solutions.

You will drive end-to-end data product development, ensuring data quality, governance, and clear ownership. Strong engagement across a matrix of stakeholders is essential for success.

Qualifications

• Experience as a subject-matter expert in Multi-Asset Solutions and Indices to develop data inputs with high value.
• 3-5 years in a role building data products or data assets (datasets, services).
• Strong ability to elicit requirements, translate business needs into data solutions, and engage stakeholders.
• Experience with data sourcing, transformation, and data governance considerations.
• Solid knowledge of data quality, metadata, and governance concepts.

Responsibilities

• Partner with business consumers to understand use cases and translate demand into data product specifications.
• Collaborate with data owners to source, transform, and validate data for ingestion and delivery.
• Lead end-to-end data product development across stakeholders and tech teams.
• Ensure data products meet governance, ownership, and audit requirements.
• Support adoption and realization of business value from data products.

Skills

Multi-Asset

Indices

Data products

Stakeholder engagement

Requirements translation

Tools

SQL

Python

JAVA

Tableau

ThoughtSpot

Job description

JPMorgan Chase seeks a Data Strategy Lead for the Multi-Asset Solutions group in New York. You will partner with research and portfolio management teams to shape data products, dashboards, and decision-support tools, coordinating with data owners and technology partners to deliver fit-for-purpose solutions.

You will drive end-to-end data product development, ensuring data quality, governance, and clear ownership. Strong engagement across a matrix of stakeholders is essential for success.