Vice President – Strategy Lead for Data Development Lifecycle (DDLC)

JPMorgan Chase & Co.•New York, NY

60d•$128,250 - $205,000

About The Position

The Chief Data Office helps teams across the firm maximize the value of data through strong governance, clear standards, and scalable delivery practices. This role is within a team focused on improving how data and AI solutions move from idea to production with the right controls and a strong practitioner experience. The role offers broad exposure across product, engineering, architecture, and risk partners, with opportunities to shape how teams build and operate data products at scale. As a Vice President-Strategy Lead for Data Development Lifecycle in the Chief Data Office, the individual will define and drive adoption of the target-state Data Development Lifecycle across the firm. They will establish standards, reference patterns, and user-centric ways of working that enable safe and efficient data and AI development at scale. The role involves partnering with business, corporate function, and technology stakeholders to remove execution friction and deliver measurable lifecycle improvements through influence. Success requires fluency in modern data science and data engineering practices, along with strong communication and operating-model leadership. The individual will help connect experimentation-to-production workflows with consistent environments, automated testing, release governance, and production support models. The role balances speed and control by embedding controls-by-design and automation-first approaches into how teams develop, validate, release, and operate data products.

Requirements

At least eight years of experience in financial services, management consulting, and/or large-scale data or technology transformation
Strong technical fluency across data analytics, data science, data engineering, and modern data platforms, with the ability to translate between practitioners and senior stakeholders
Practical knowledge of data product concepts and modern distributed data patterns, including integration between software and data development lifecycles
Demonstrated experience driving cross-functional operating model or process change and scaling adoption across multiple organizations
Demonstrated ability to influence stakeholders and align diverse groups without direct authority
Strong written and verbal communication skills, including executive-level communication of complex technical topics
Experience improving lifecycle capabilities for data products, including continuous integration and delivery enablement, environment promotion strategies, automated testing approaches, release governance, and production support operating models
Experience partnering with engineering and platform teams to deliver measurable workflow improvements (for example: reduced onboarding time, faster release cadence, improved reliability, and increased control automation coverage)

Nice To Haves

Experience supporting data science and AI development workflows (for example: reproducibility, model validation, monitoring, and experimentation-to-production practices)
Experience designing or scaling control frameworks that improve compliance outcomes while reducing practitioner friction
Experience working in a large, highly regulated environment with complex technology landscapes
Experience developing reusable reference patterns and standards that improve developer experience and consistency

Responsibilities

Define and continuously improve the target-state data development lifecycle across intake, design, build, test, release, and run, including decision rights and exception management
Partner with architecture and engineering leaders to establish reference architectures and reusable patterns that enable secure, controlled development and testing environments
Drive roadmap, adoption, and outcomes for lifecycle-enabling platforms and toolchains by translating practitioner needs into clear product requirements, prioritization, and rollout plans
Enable adoption through playbooks, training, communications, change champions, and practitioner feedback loops
Embed and automate controls-by-design into the lifecycle in partnership with risk and control stakeholders, using automation-first approaches where possible
Facilitate cross-functional working groups to align stakeholders and remove execution friction across product, engineering, architecture, risk, and controls
Identify, escalate, and help mitigate risks and dependencies that could impair strategy execution; manage trade-offs and sequencing
Produce executive-ready materials to communicate complex concepts and drive decisions with senior leadership
Operate independently in a highly collaborative, matrixed environment to build consensus and deliver measurable change