Elevate your career by steering multi-faceted tech programs, integrating innovative solutions for a dynamic impact across global operations.

The Chief Data & Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm’s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm’s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.

• As a Lead Technical Program Manager at JPMorgan Chase in AIML Data Platforms
• Chief Data Analytics Office, you will lead complex, multi-functional technology projects and programs that will impact experiences for multiple groups across the firm, including clients, employees, and stakeholders. With your advanced analytical reasoning and adaptability skills will enable you to break down business, technical, and operational objectives into manageable tasks, while navigating through ambiguity and driving change. With demonstrated technical fluency, you will effectively manage resources, budgets, and cross-functional teams to deliver innovative solutions that align with the firm's strategic goals. Your exceptional communication and influencing abilities will foster productive relationships with stakeholders, ensuring alignment and effective risk management. In this pivotal role, you will contribute to the development of new policies and processes, shaping the future of our technology landscape.

Job responsibilities

• Creates and maintains detailed project plans, timelines, and delivery schedules for assigned programs
• Manages day-to-day program execution using JIRA, Confluence, and other project management tools, ensuring accurate tracking of user stories, epics, and sprint progress
• Facilitates agile ceremonies including sprint planning, daily standups, retrospectives, and backlog grooming sessions with engineering teams
• Maintains comprehensive program documentation including status reports, risk registers, RAID logs, and dependency matrices
• Oversees engineering risks, issues, dependencies for assigned programs
• Engages with stakeholders including customers within the lines of businesses
• Guides the selection and implementation of appropriate technologies, platforms and software tools leveraging technical fluency
• Champions continuous improvement by identifying process optimization opportunities, incorporating best practices, and staying abreast of emerging technologies
• Partners with the product organization to drive business outcomes, ensuring that technical programs are aligned with strategic business goals
• Prepares and deliver regular status updates and presentations to program stakeholders and leadership to communicate progress, risks, and blockers

Required qualifications, capabilities, and skills

• 5+ years of experience or equivalent expertise in technical program management, leading complex technology projects and programs in large organizations
• Hands-on experience with agile project management tools (JIRA, Confluence, MS Project) and proven ability to maintain accurate program artifacts and metrics
• Demonstrated proficiency in technical solutions, vendor product knowledge, managing vendor relations, and implementing solutions
• Strong analytical reasoning skills, applying critical thinking and problem-solving techniques to break down business, technical, and operational objectives
• Proven ability in leading through change, managing dependencies, and controlling change in high-pressure, shifting environments
• Strong skills in stakeholder management, establishing productive relationships, and driving beneficial outcomes aligned with firm objectives
• Understanding of data platform trade-offs including performance optimization, cost management, scalability, and operational excellence
• Deep technical understanding of modern data platform architectures including data lakes, data warehouses, lakehouse architectures, and distributed computing frameworks
• Experience with enterprise-scale implementations of cloud-native data platforms such as Databricks and Snowflake
• Good understanding of AWS data analytics services including Redshift, EMR, Glue, Athena, Kinesis, Lake Formation, MSK, and S3