Technical Product Manager

1 week ago

Mumbai, Maharashtra, India JPMorganChase Full time US$ 1,50,000 - US$ 2,00,000 per year

Join our team to elevate your product management career in data engineering.

As a Technical Product Manager within the Credit Card Data & Analytics team, you will drive the build-out of data engineering solutions, including data products and GenAI tools. You will translate technical requirements into business needs, working with tech teams on data publishing using tools like PySpark and environments like AWS S3, Snowflake, and Data Bricks.

Job Responsibilities:

  • Create business cases through Product Review Documents and drive execution through initiatives, epics, and NFRs in JIRA.
  • Identify and engage stakeholders to ensure table design, data models, and robust data context and descriptions are a key part of all requirements.
  • Manage and coordinate the work of 5+ scrum teams, ensuring alignment with business goals and technical requirements.
  • Dive deep into understanding data flows and translate technical requirements into business needs and vice-versa.
  • Work with tech teams on data publishing using data engineering tools like PySpark.
  • Serve as the India lead for the Card Data Product Team and drive the build-out of data engineering solutions, including data products and GenAI tools.

Required Qualifications, Capabilities, and Skills:

  • Minimum 7 years of industry experience in product management and a data-related field.
  • Strong ability to articulate business cases from technical details with ease, managing senior stakeholders while also diving deep into data engineering.
  • Demonstrated ability to manage tight delivery timelines across multiple workstreams, ensuring the organization is on track to execute and deliver strategic changes.
  • Strong understanding of agile methodologies and experience with them.
  • Structured thinker and effective communicator with excellent written communication skills.

Preferred Qualifications, Capabilities, and Skills:

  • Familiarity with different data environments such as AWS S3, Snowflake, and Data Bricks.
  • Technical knowledge of data engineering, data pipelines, data modeling, and data architecture preferred.

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