Associate Data Owner-US Wealth Management

JPMorgan Chase & Co.; Columbus (OH); On-site; USD 85,000 - 110,000; Full time

Job summary

JPMorgan Wealth Management is seeking an Associate Data Owner to enable end-to-end product data governance and publishing. You will work with a VP Data Owner to define business definitions, metadata, classifications, and quality expectations, ensuring data is discoverable, understandable, and fit for purpose across analytics teams.

You will support data enablement, monitor quality, track data lineage, and coordinate cross-functional activities to reduce data risk in a fast-paced, Agile

Qualifications

• 3+ years of experience in data delivery, analytics enablement, data governance, or adjacent roles.
• Use SQL to analyze data, validate quality, and support investigations across relational or big data platforms.
• Demonstrate ability to execute reliably in a fast-paced, stakeholder-rich environment with clear follow-through.
• Communicate effectively with both technical and non-technical partners via written updates and presentations.
• Think analytically, breaking down ambiguous problems into actionable steps and measurable outputs.
• Manage multiple priorities with strong organization, attention to detail, and time management.
• Learn quickly and apply feedback to improve deliverables and operating routines.
• Hold a Bachelor’s degree or equivalent experience.

Responsibilities

• Support the product’s data agenda across creation, ingestion, publishing, and consumption.
• Assist in establishing data quality requirements and monitoring for accuracy, completeness, timeliness, and lineage.
• Support delivery of data pipelines and products by tracking dependencies, coordinating handoffs, and reinforcing Agile execution across workstreams.
• Document business definitions, metadata, and classifications so critical data is discoverable and consistently understood.
• Maintain data governance artifacts such as inventories, controls evidence, and procedures to support ongoing compliance and audit readiness.
• Perform data profiling and validation to identify anomalies, gaps, and trends impacting downstream use.
• Partner with technology and data delivery teams to support root cause analysis and remediation execution.
• Communicate updates, risks, and decisions through well-structured documentation and stakeholder routines.
• Contribute to continuous improvement by identifying process bottlenecks and proposing pragmatic fixes.

Skills

SQL

Data governance

Analytical thinking

Communication

Time management

Education

Bachelor’s degree or equivalent experience

Tools

Python

ETL tooling

Data catalogs

Data lineage tools

Job description

If you like making complex data clearer, safer, and easier for teams to use, this role is for you.JPMorgan Wealth Management needs passionateData Owner Associatesto support product data end-to-end—help make it trusted, well-governed, and ready to power analytics and delivery. You’llsupport a single product’s data enablement, publishing, and governance—working alongside a VP Data Owner to keep priorities moving and turn data into reliable outcomes.

As an Associate Data Owner on the US Wealth Management Data & Analytics team, you support end-to-end enablement, publishing, and governance for all data created and used by an aligned product under the direction of a VP Data Owner. You help define and document product data—business definitions, metadata, classifications, and quality expectations—so it is discoverable, understood, and fit for purpose. You assist with monitoring, issue management, and cross-functional coordination to improve data quality and reduce data risk across the lifecycle.

Job Responsibilities

• Support the product’s data agenda across creation, ingestion, publishing, and consumption
• Assist in establishing data quality requirements and monitoring for accuracy, completeness, timeliness, and lineage.
• Support delivery of data pipelines and products by tracking dependencies, coordinating handoffs, and reinforcing Agile execution across workstreams.
• Document business definitions, metadata, and classifications so critical data is discoverable and consistently understood
• Maintain data governance artifacts such as inventories, controls evidence, and procedures to support ongoing compliance and audit readiness
• Perform data profiling and validation to identify anomalies, gaps, and trends impacting downstream use
• Partner with technology and data delivery teams to support root cause analysis and remediation execution
• Communicate updates, risks, and decisions through well-structured documentation and stakeholder routines.
• Contribute to continuous improvement by identifying process bottlenecks and proposing pragmatic fixes

Required Qualifications, Capabilities and Skills

• 3+ years of experience in data delivery, analytics enablement, data governance, or adjacent roles
• Use SQL to analyze data, validate quality, and support investigations across relational or big data platforms
• Demonstrate ability to execute reliably in a fast-paced, stakeholder-rich environment with clear follow-through
• Communicate effectively with both technical and non-technical partners via written updates and presentations.
• Think analytically, breaking down ambiguous problems into actionable steps and measurable outputs
• Manage multiple priorities with strong organization, attention to detail, and time management
• Learn quickly and apply feedback to improve deliverables and operating routines.
• Hold a Bachelor’s degree or equivalent experience

Preferred Qualifications, Capabilities and Skills

• Bring experience in financial services, wealth management, or client/advisor data domains
• Utilize data catalogs, lineage tools, and data quality monitoring solutions
• Apply experience working with Agile teams and participating in ceremonies (planning, standups, retrospectives, etc.)
• Leverage exposure to CRM and sales platforms (e.g., Salesforce) and related data flows
• Use Python or ETL tooling for profiling, wrangling, and repeatable data quality checks
• Demonstrate understanding of data governance, data ethics, and responsible data use in regulated environments
• Embrace a growth mindset and continuous learning of modern data patterns and tooling