Product Manager [Multiple Positions Available]

DESCRIPTION:

Duties: Develop and implement new features to enhance the capabilities of Data Lake for analytics, AI, and ML use cases.

Coordinate deliverables with data owners, data engineers, and required stakeholders to ensure timely progress on key projects and initiatives.

Assess the current state of Data Lake datasets and identify opportunities for improvement and innovation in data storage, data processing, and data catalog services.

Develop and maintain comprehensive roadmaps that align with strategic objectives.

Prioritize the evolution of data assets for Data Lake publication and consumption.

Collaborate with cross-functional teams, including data engineers and data scientists, to design and deliver scalable solutions that meet business needs.

Monitor industry trends and emerging technologies to inform product development and maintain a competitive edge in data management and analytics.

Communicate with stakeholders to provide updates on project status, gather feedback, and ensure alignment with organizational goals.

This position requires up to 20% domestic travel to other JPMC worksites.

QUALIFICATIONS:

Minimum education and experience required: Master's degree in Computer Science, Computer Engineering, Information Technology, Mathematics, or related field of study plus 5 years of experience in the job offered or as Product Manager, Systems Development Engineer, Big Data Architect/Support Engineer, or related occupation.

The employer will alternatively accept a Bachelor's degree in Computer Science, Computer Engineering, Information Technology, Mathematics, or related field of study plus 7 years of experience in the job offered or as Product Manager, Systems Development Engineer, Big Data Architect/Support Engineer, or related occupation.

Skills Required: This position requires experience with the following: Coordinating and managing the product lifecycle from ideation to deployment; Translating technical concepts into product requirements and user stories for data lake architectures, transactional processing, and data analytics; Managing the storage and governance of datasets using AWS Lake Formation and S3; Publishing datasets using Spark and Python via AWS Glue, EMR, and EKS; Validating auditability and observability of datasets leveraging CloudWatch and Cloudtrail; Providing infrastructure for datasets using Terraform and CI/CD processes; Providing visibility into consumption using Business Insights (BI) and analytical tools including Amazon Athena and AWS Quicksight; Communicating insights derived from data using data visualization and analysis tools including Datadog, Prometheus, and Grafana; Forecasting trends, costs, and customer behaviors using regression analysis and time series forecasting; Building scalable, governable, and interoperable data lake products using data and analytics services including Apache Spark and large-scale processing engines; Developing customers use cases using ML/AI frameworks including Tensorf...