Finance Data Insights Release Management -Vice President

JPMorgan Chase & Co.•Newark, DE

About The Position

Join the Finance Data Insights Release Management team and lead high-impact releases across Finance data products that support internal financial reporting and external regulatory reporting. You’ll help us move fast while managing change in a controlled, audit-ready manner to meet business and regulatory timelines. As a Vice President, Release Manager in the Finance Data Insights Release Management team, you will lead end-to-end planning and execution of change events across Finance data platforms (data warehouse and data lake environments). You will improve release health, reliability, and stakeholder experience by driving automation, standardization, and artificial-intelligence-assisted ways of working (for example, faster detection, triage, and investigation of data anomalies and release issues). You will partner across products and teams to deliver outcomes that are controlled, well-evidenced, and aligned to delivery timelines.

Requirements

Bachelor’s degree and 5+ years of experience in release/change management, program/project management, or related delivery roles
Demonstrated experience managing release/change events with strong attention to risk, controls, and stakeholder impact.
Strong data analytics skills, including ability to query and analyze data to support validation and issue investigation; advanced Excel (or equivalent analytical tooling).
Experience coordinating testing and quality validation (for example, regression testing, reconciliations, data quality checks) and leading root-cause analysis.
Proven stakeholder management skills (influencing, negotiation, expectation management) and strong data storytelling; strong written and verbal communication with ability to tailor messages by audience.
Advanced skills in metrics, reporting, and presentation creation, including executive-level PowerPoint outputs.
People leadership experience (coaching, prioritization/capacity planning, performance feedback) and experience using artificial-intelligence-assisted analytics tools and/or automation to accelerate delivery and improve performance (for example, anomaly detection, regression testing acceleration, smarter alerting/triage, faster investigation and root-cause analysis, improved data quality monitoring).

Nice To Haves

Agile delivery mindset; experience using Jira and working knowledge of Jira Query Language (JQL).
Experience in Financial Services and/or a Consulting background.
Experience with modern data platforms and tooling, including Databricks.
Familiarity with Data Mesh concepts and/or cloud strategy.

Responsibilities

Own end-to-end release and change execution across Finance data platforms, covering both planned and ad hoc change events; coordinate and execute testing and quality activities (including regression testing and anomaly detection) to validate changes align with requirements and expected outcomes.
Drive high-velocity, well-controlled change by ensuring governance, approvals, documentation, and evidence are completed without slowing delivery.
Identify, assess, and escalate risks and issues with clear options, impacts, and mitigation plans; drive timely decision-making and support faster recovery when needed.
Lead stakeholder management across the lifecycle—setting expectations, negotiating scope and timelines, and tailoring communications to varied audiences.
Lead and develop a team, including coaching, prioritization and capacity planning, and performance feedback to deliver consistent release outcomes and foster a strong controls culture.
Embed artificial-intelligence-assisted analytics and automation into release execution and quality controls to accelerate anomaly detection, regression testing, issue triage, and root-cause investigation; partner with data engineering and platform to improve data quality monitoring, observability, and proactive risk identification ahead of releases.
Establish and track operational key performance indicators (for example, release lead time, change failure rate, defect leakage, rework, incident volumes, automation coverage); use insights to prioritize continuous improvement, standardize processes, reduce manual effort, improve cycle times, increase predictability, and produce executive-ready materials (updates, metrics, decision decks) while program-managing key modernization initiatives through disciplined planning, reporting, and delivery governance.