Lead Technical Program Manager - Aiml- Databricks

JPMorgan Chase JPMorgan Chase · Banking · Jersey City, NJ +1 · Corporate Sector

Lead Technical Program Manager for AIML Data Platforms within JPMorgan Chase's Chief Data & Analytics Office. This role focuses on managing complex, cross-functional technology programs related to data and AI/ML platforms, ensuring alignment with strategic goals, managing resources, and driving continuous improvement. The role requires strong technical program management skills, agile methodologies, and an understanding of modern data architectures and cloud platforms.

What you'd actually do

  1. Creates and maintains detailed project plans, timelines, and delivery schedules for assigned programs
  2. Manages day-to-day program execution using JIRA, Confluence, and other project management tools, ensuring accurate tracking of user stories, epics, and sprint progress
  3. Facilitates agile ceremonies, including sprint planning, daily standups, retrospectives, and backlog grooming, with engineering teams
  4. Maintains comprehensive program documentation, including status reports, risk registers, RAID logs, and dependency matrices
  5. Oversees engineering risks, issues, and dependencies across assigned programs

Skills

Required

  • technical program management
  • agile delivery tools (JIRA, Confluence)
  • planning tools (e.g., MS Project)
  • technical solutioning
  • vendor product evaluation
  • vendor management
  • solution implementation
  • analytical reasoning
  • critical thinking
  • problem-solving
  • stakeholder management
  • modern data platform architectures
  • data lakes
  • data warehouses
  • Lakehouse architectures
  • distributed computing frameworks
  • Databricks
  • Snowflake
  • AWS data analytics services
  • Redshift
  • EMR
  • Glue
  • Athena
  • Kinesis
  • Lake Formation
  • MSK
  • S3 data lake patterns
  • data governance
  • security
  • compliance requirements

Nice to have

  • steering multi-faceted technology programs
  • integrating innovative solutions
  • driving impact across global operations
  • leading complex, cross-functional technology programs
  • navigating ambiguity
  • driving change
  • managing resources
  • managing budgets
  • managing cross-functional teams
  • fostering productive stakeholder relationships
  • ensuring alignment
  • effective risk management
  • contributing to new policies and processes
  • shaping the future of our technology landscape
  • performance optimization
  • cost management
  • scalability
  • operational excellence
  • architecting end-to-end data solutions

What the JD emphasized

  • 5+ years of experience (or equivalent expertise) in technical program management, leading complex technology initiatives in large organizations
  • Hands-on experience with agile delivery tools (JIRA, Confluence) and planning tools (e.g., MS Project), with proven ability to maintain accurate program artifacts and metrics
  • Demonstrated proficiency in technical solutioning, vendor product evaluation, vendor management, and solution implementation
  • Strong analytical reasoning skills, applying critical thinking and problem-solving techniques to break down business, technical, and operational objectives
  • Proven ability to lead through change, manage dependencies, and control scope in high-pressure, shifting environments
  • Strong stakeholder management skills, building productive relationships and driving outcomes aligned with firm objectives
  • 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 data lake patterns, with demonstrated experience architecting end-to-end data solutions
  • Experience navigating complex data governance, security, and compliance requirements across multi-cloud and hybrid data environments at enterprise scale