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Global Security – Consumer Security Operations - Product Delivery Manager

JPMorgan Chase
Ohio, USA
Full-time
Manager
Onsite
Discovered 1 weeks ago
awsazureazure-data-factorybigqueryconfluencedatabricks

Full Job Posting

Job Responsibilities

  • Own the day-to-day delivery cadence for GMP, including delivery planning, backlog readiness, dependency coordination, and issue triage through completion.
  • Develop and maintain delivery plans, timelines, milestones, decision logs, risk/issue logs, and stakeholder-ready status reporting.
  • Gather business, operational, and technical requirements; translate needs into epics, user stories, acceptance criteria, and supporting documentation in Jira/Confluence.
  • Coordinate Agile execution (planning, refinement, reviews, demonstrations) and track/resolve blockers and cross-team dependencies.
  • Coordinate testing and release readiness activities (functional testing coordination, end-to-end test planning, UAT readiness, defect intake, fallback planning, production validation coordination).
  • Provide delivery support for UEM and the CS Data Lake, including tracking work items, coordinating dependencies, and supporting readiness activities aligned to the portfolio roadmap.
  • Track product health signals and recurring issues; coordinate vendor issues (as applicable) and ensure defects/recurring problems are logged and progressed.
  • Cross-product reporting, governance, CS surveys, data ecosystem dependencies, control documentation, training, and coverage during peak delivery cycles, and support future Consumer Security products.

Required qualifications, capabilities, and skills

  • Bachelor’s degree in Computer Science, Information Technology, or a related field, or equivalent relevant experience.
  • Experience supporting product delivery, technology delivery, business analysis, project management, SaaS platforms, or operational change initiatives.
  • Proficiency with Jira and Confluence, with strong technical writing skills to clearly translate complex information for diverse stakeholders.
  • Strong analytical and problem-solving skills, with excellent attention to detail and the ability to analyze detailed business requirements; experience with business intelligence and analytics tools (e.g., Tableau, Power BI, Qlik, Looker, Databricks) and utilizing large language models (LLMs).
  • Moderate proficiency in SQL, with experience using data integration technologies and performing data analysis.
  • Demonstrated project management skills with experience in Agile methodologies, including managing epics and user stories within Jira.
  • Excellent communication skills, capable of presenting complex data concepts to both technical and non-technical audiences.
  • Ability to work with large and complex systems and datasets, ensuring data quality and integrity through rigorous testing and validation processes.
  • Proficiency in at least one cloud data lake platform (e.g., Databricks Lakehouse, AWS Lake Formation, ThoughtSpot), relevant data services (e.g., AWS S3, Redshift; Azure Data Factory; Google Cloud BigQuery), and one scheduling/orchestration tool.
  • Experience in data engineering, modeling, and cloud architecture design, with a focus on building solutions for data lineage, metadata management, and data quality improvements.
  • Demonstrated knowledge of data integration principles, including foundational concepts, patterns, best practices, API-first design methodologies, GraphQL, and Kafka services.
  • Experience building intelligent analytics products utilizing AI/ML techniques.
  • Exposure to security or real estate operations, including understanding physical security, investigation processes, and incident management, to support data responsibilities.
  • Certification or Accreditation in data management or data governance (e.g., CDMP, DGSP).
  • Demonstrated curiosity and initiative to explore data, identify root causes, and uncover opportunities for efficiency improvements.

Preferred qualifications, capabilities and skills

  • Proficiency in at least one cloud data lake platform (e.g., Databricks Lakehouse, AWS Lake Formation, ThoughtSpot), relevant data services (e.g., AWS S3, Redshift; Azure Data Factory; Google Cloud BigQuery), and one scheduling/orchestration tool.
  • Experience in data engineering, modeling, and cloud architecture design, with a focus on building solutions for data lineage, metadata management, and data quality improvements.
  • Demonstrated knowledge of data integration principles, including foundational concepts, patterns, best practices, API-first design methodologies, GraphQL, and Kafka services.
  • Experience building intelligent analytics products utilizing AI/ML techniques.
  • Exposure to security or real estate operations, including understanding physical security, investigation processes, and incident management, to support data responsibilities.
  • Certification or Accreditation in data management or data governance (e.g., CDMP, DGSP).
  • Demonstrated curiosity and initiative to explore data, identify root causes, and uncover opportunities for efficiency improvements.
  • Preferred qualifications, capabilities and skills

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