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JP Morgan Chase

Runs a consumer bank and an investment bank

Data Owner Lead - Data Management Operations, Vice President

Data ManagementConfirmed live in the last 24 hours
Full-timeJersey City, NJ, USA$133k - $205kIn-person

About the Job

Requirements

  • A bachelor's degree in Data Science, Computer Science, Information Systems, or Data Analytics, or equivalent professional experience.
  • Five years of experience in data management, data governance, or risk management/analytics, including demonstrated experience delivering or closely partnering on delivery of data products or curated datasets that integrate multiple sources for enterprise consumption.
  • A proven leadership track record and ability to manage delivery timelines.
  • In-depth understanding of data management principles and governance frameworks, working knowledge of the data development lifecycle, and familiarity with the build, release, run, and change operating model for data products.
  • Ability to translate consumer needs into clear data requirements, acceptance criteria, and measurable quality, usability, and adoption outcomes.
  • Experience building relationships with key stakeholders and managing large-scale data projects.
  • Experience with cloud-based data platforms such as AWS, Azure, or Google Cloud, data lake or lakehouse concepts, and information architecture practices.
  • Familiarity with advanced analytics, machine learning, or AI applications, and hands-on experience leveraging large language models for productivity and governance automation, including prompt engineering patterns, agent/tooling concepts, and evaluation or monitoring of outputs.
  • Knowledge of query or analytical programming languages such as SQL; Oracle is a plus, and comfort partnering with engineering on ingestion and transformation patterns.
  • Experience leading digital transformation initiatives leveraging data.
  • Experience in data product management and establishing operating processes for data products, including documentation standards, quality SLAs/SLOs, monitoring/alerting, and lifecycle/deprecation.

Responsibilities

  • Implement strategic plans to deliver data solutions and data products that support business operations and strategic objectives.
  • Manage project execution and mitigate risks and inefficiencies.
  • Collaborate with partners to document and classify critical data with metadata, ensuring metadata supports discovery and reuse, including business definitions, technical metadata, lineage, quality rules and thresholds, and product documentation.
  • Provide subject matter expertise on data content and usage within the business and associated product areas.
  • Develop relationships with data providers and consumers across multiple functions; engage consumer populations across operations, reporting, analytics, and data science to understand usage patterns and improve the usability of curated datasets and data products.
  • Document requirements for data sourcing, content, and quality; define requirements for integrating multiple upstream sources, including mapping, transformation logic, and reconciliation, and for building curated datasets for analytics and reporting use cases.
  • Develop processes to identify and mitigate data risks throughout the data lifecycle, including data protection, privacy, retention, destruction, storage, use, and quality; operationalize controls within pipelines and data products, such as automated quality checks, monitoring/alerting, and auditable evidence.
  • Support data analytics by governing data integration into analytics platforms, including designing fit-for-purpose curated datasets and feature-ready data products for advanced analytics and machine learning use cases.
  • Communicate and resolve data issues, maintain data integrity, and support issue triage and root-cause analysis with business and technology partners; drive remediation and preventative controls to reduce recurrence.
  • Leverage AI, machine learning, and large language model tooling to automate governance and data management activities, including metadata drafting/classification, control evidence generation, quality rule suggestions, and lineage/documentation assistance; create and evaluate prompts and contribute to agent-based workflow designs where appropriate.

Desired Qualifications

  • Experience with cloud-based data platforms such as AWS, Azure, or Google Cloud, data lake or lakehouse concepts, and information architecture practices.
  • Familiarity with advanced analytics, machine learning, or AI applications, and hands-on experience leveraging large language models for productivity and governance automation, including prompt engineering patterns, agent/tooling concepts, and evaluation or monitoring of outputs.
  • Knowledge of query or analytical programming languages such as SQL; Oracle is a plus, and comfort partnering with engineering on ingestion and transformation patterns.
  • Experience leading digital transformation initiatives leveraging data.
  • Experience in data product management and establishing operating processes for data products, including documentation standards, quality SLAs/SLOs, monitoring/alerting, and lifecycle/deprecation.

About the Company

JP Morgan Chase

Runs a consumer bank and an investment bank

JPMorgan Chase runs the largest bank in the United States, which serves households and small businesses as Chase and large companies, governments, and investors as J.P. Morgan. During the 2008 financial crisis it bought the failing investment bank Bear Stearns and lender Washington Mutual, and in 2023 it took over First Republic Bank after regulators seized it. Chase takes deposits and earns interest on credit cards, mortgages, and car loans, while the investment side earns fees for advising on mergers, raising money for companies, trading stocks and bonds, and managing wealth. Formed in a 2000 merger, JPMorgan Chase traces its roots to 1799 and is based in New York City.

Company size
10,001+
Company stage
IPO
Headquarters
New York City, New York
Founded
1799

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