Live opening · Posted 5 days ago

Product Delivery Associate – Data Products & Analytics

JPMorgan Chase · BOURNEMOUTH, DORSET, United Kingdom | LONDON, United Kingdom
Oracle
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanyJPMorgan Chase
LocationBOURNEMOUTH, DORSET, United Kingdom | LONDON, United Kingdom
SourceOracle
Listed5 days ago

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About the role

Description supplied by the original job listing.

Play a crucial role in transforming ideas into functional products, while navigating through complex challenges. Develop your skills, contribute to meaningful change, and propel your career in an environment that values growth and learning.
As a Product Delivery Associate in Corporate Sector, you enable the release of products and features by overcoming obstacles. As an emerging member of the team, you work across the organization and enable the product to continuously deliver value, while gaining skills and experience to grow within your role.
Job responsibilities
Support end-to-end delivery processes: intake, dependency management, release management, product operationalization, delivery feasibility decision-making, and product performance reporting; identify and drive efficiency opportunities.
Contribute to change management across functional partners; document adherence to firm risk, controls, compliance, and regulatory requirements.
Document blockers and impediments to support dependency management and resource availability planning.
Partner with the Product Delivery Manager to engage stakeholders and cross-functional teams to manage dependencies and timelines.
Document transformation requirements and support enhanced data-product designs.
Identify opportunities to centralize business logic (shared, reusable calculation rules) across data products.
Support development of report-focused views and semantic layers (business-friendly data models) to improve consumption and reduce duplication.
Support launch and adoption of AI-enabled analytics tooling (e.g., Databricks Genie and other prompt-based AI-assisted analytics), including user enablement, curated data rooms, training coordination, and optimizing data views for AI tools.
Review and triage incoming feature requests and new demand; clarify requirements and route work to the appropriate product and technology partners.
Maintain and prioritize Jira items with Associate Product Owners and technology teams; assess readiness and sequencing; run and document Agile ceremonies (discovery, sprint planning, sprint review).
Troubleshoot user inquiries and provide first-line support to data-product users; capture requirement gaps; review draft data contracts for completeness/fit; test enhancements and advise on end-user reporting queries to encourage reuse of centralized logic.
Required qualifications, capabilities, and skills
A Bachelor’s degree in Computer Science, IT, Business, Finance, Data Analytics, or a related field, or equivalent experience in product management, project management, or a relevant domain area
Demonstrated experience or equivalent expertise in product management, project management, or a relevant domain area
Exposure to operational management and change readiness workstreams
Experience in data management, analytics, or product delivery.
Ability to elicit and write up requirements clearly enough for a developer to build from.
Comfort working with large data sets, including checking data quality and supporting testing.
Working familiarity with SQL, Python, or a similar data-analysis language.
Ability to explain technical topics to non-technical people.
Preferred qualifications, capabilities, and skills
Experience with Finance and Business Management processes that support technology teams.
Hands-on use of BI or analytics tools such as Alteryx, Tableau, Databricks, or Sigma.
Exposure to Agile delivery and Jira-based routines.
Experience supporting data-product users through triage, guidance, or training.
Exposure to data contracts, semantic-layer design, or downstream reporting transformation.
Interest in AI-enabled data consumption, such as prompt-based analytics or curated data rooms.
Knowledge of cloud-based data or lakehouse platforms such as Databricks.

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