
Posted 16 days ago
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JPMorgan Chase's Firmwide Chief Data Office is seeking a Data Management Lead to drive and execute firmwide data strategy, focusing on semantic mapping, policy integration, and AI enablement. The role involves developing models and semantic applications (including RDF/graph technologies), drafting product and engineering requirements, and collaborating across lines of business and corporate functions. You will lead program execution, communicate recommendations to executive stakeholders, and implement data strategy solutions at scale to improve data discoverability and usability for people and tools.
- Compensation
- Not specified
- City
- Hyderabad
- Country
- India
Currency: Not specified
Full Job Description
Location: Hyderabad, Telangana, India
Are you passionate about driving data strategy at scale ?Join our Firmwide Chief Data Office and help maximize the value and impact of data across JPMorgan Chase. In this high-profile role, you will collaborate with leading teams to power innovation, product development, and AI models through effective data enablement. Be part of a team accelerating our data, analytics, and AI journey.
As a Data Management Lead in the Firmwide Chief Data Office, you will help to develop and prove our data strategy, focusing on development of models and solutions covering semantic mapping, policy integration, and AI solutions to make our data easy to understand for humans to tools. You will interact with teams across the firm, including lines of business and corporate functions, and play an instrumental role in planning, collaborating, and building complex data strategy products. You will communicate effectively with leadership and stakeholders, guide team members, help draft product requirements, and take ownership of data strategy concepts that impact end user products.
Job responsibilities:
- Lead and own day-to-day execution of data strategy programs across the firm
- Develop written materials to articulate data strategy and initiatives
- Draft product requirements and engineering requirements
- Build strong relationships and inspire followership within a consensus-driven team environment
- Gather and analyze information, formulate and test hypotheses, and develop recommendations for executive leaders and Chief Data Officers
- Implement decisions and recommendations across the firm with team members
- Identify and mitigate risks, proactively addressing potential roadblocks and implementing contingency plans
- Utilize advanced analytical reasoning to assess program performance and implement data-driven optimizations
- Facilitate effective communication across teams, ensuring alignment on priorities and objectives
- Provide regular status updates to key stakeholders and leadership
Required qualifications, capabilities, and skills:
- 5+ years of data architecture, modelling, engineering experience in global/firmwide environments
- Experience with semantic web technologies and standards, comfortable with knowledge graph concepts and applications
- Experience with data integration, mapping, ontology development at scale
- Hands on with graph and specifically RDF based graph technology
- Hands on development experience building semantic applications, services, databases
- Develop professional written materials and executive level presentations
- Manage to work collaboratively in a team of data experts and create an inclusive environment at all levels
- Expertise in stakeholder management, with the ability to establish productive relationships and influence decision-making
- Experience to break down and solve problems through quantitative thinking and analysis
- Intellectual curiosity, strategic thinking, and strong project management skills
- Passion for data strategy
Preferred qualifications, capabilities, and skills:
- Experience upskilling colleagues in a rapid manner
- Proven ability to communicate effectively with leadership and key stakeholders about wins, use cases, risks, issues, and statuses
- Strong interpersonal and communication skills, ensuring successful program outcomes and team performance
- Data Engineering and architecture background





