Product Director [multiple Positions Available]

JPMorgan Chase JPMorgan Chase · Banking · Seattle, WA +1 · Consumer & Community Banking

Product Director role at JPMorgan Chase focused on leading the product lifecycle for AI solutions within the CCB data and data engineering productivity domain. The role involves defining product vision and strategy, overseeing roadmaps, partnering with tech teams, and ensuring successful delivery of AI-powered products, leveraging AWS cloud services.

What you'd actually do

  1. Lead the entire product lifecycle through planning, execution, and future development phases.
  2. Continuously develop and adapt new products and methodologies while managing risks and achieving business targets like cost, features, reusability, and reliability to support business growth.
  3. Analyze customer's product requirements against competitive market trends in order to define and communicate the Area Product vision and strategy.
  4. Identify and implement opportunities to build artificial intelligence (AI) solutions that power CCB data and enhance data engineer productivity.
  5. Partner closely with technology and architecture teams on concept development, proof of concepts, and capability development.

Skills

Required

  • technology products and application integrations between external applications to data platforms
  • data conversions and data migrations including data cleansing, validation, reconciliation and cutover, and APIs
  • system design and architecture
  • microservices architecture
  • working with engineers and architects to define integration contracts and non-functional requirements to deliver integrated and scalable enterprise-grade solutions
  • managing the full product lifecycle from ideation, discovery, and fit-gap analysis through design, build, test, deployment, adoption, and ongoing support
  • writing RFP responses
  • requirement gathering
  • translating complex technical concepts into clear business and product requirements
  • translating business requirements into technical design, user stories, and implementation plans
  • applying data-driven decision-making using large-scale datasets
  • defining success metrics
  • performing business reporting
  • leading cross-functional teams either as a direct manager or as a functional team lead driving project roadmap, prioritization, and delivery
  • user and stakeholder engagement including interacting with end users for requirements and user acceptance testing (UAT)
  • liaising with executives and cross-functional stakeholders to align on project delivery scope, risk, and timelines
  • delivering technology solutions using six sigma quality standards including adherence to security, privacy, compliance, reliability, cost efficiency, and technology guardrails
  • cross-functional delivery on cloud platform AWS
  • data and analytics cloud technologies including AWS S3, API Gateway, Athena, Glue, EKS, and Apache Iceberg on AWS
  • leveraging cloud services Dynamo DB and Lambda to enhance product capabilities
  • large-scale AWS service migrations
  • defining customer experience flows and data capture requirements using Amazon Connect to integrate data for reporting and insights

What the JD emphasized

  • build artificial intelligence (AI) solutions
  • data engineer productivity
  • six sigma quality standards including adherence to security, privacy, compliance, reliability, cost efficiency, and technology guardrails

Other signals

  • build artificial intelligence (AI) solutions
  • power CCB data
  • enhance data engineer productivity
  • partner closely with technology and architecture teams on concept development, proof of concepts, and capability development