Data Product Manager

JR United Kingdom; Slough; Hybrid; GBP 55,000 - 80,000; Full time

Job summary

A leading consultancy is seeking a Data Product Manager to drive data product development. This role encompasses product lifecycle management from ideation to delivery, collaboration with teams, and implementation of data standards. Ideal candidates will have experience in AI/ML and strong cross-functional collaboration skills.

Qualifications

• Experience in AI/ML is required.
• Ability to work in multidisciplinary teams is essential.

Responsibilities

• Lead the end-to-end product lifecycle for data products.
• Gather requirements and communicate with end users from a product perspective.
• Develop and implement data standards for consistency across systems.

Skills

Product Strategy

Data Architecture

AI/ML

Cross-functional Collaboration

Job description

Social network you want to login/join with:

? Location: London - 2 days onsite per week or fully remote from Budapest

? Contract Duration: 6 months+

? Industry: Energy via Consultancy

About the Company: Our consultancy client is hiring for a Data Product Manager to join our dynamic team and help shape the future of our data products. This role is ideal for someone who thrives at the intersection of product strategy, data architecture, and cross-functional collaboration. You will be responsible for driving the development of scalable, high-quality data products that meet the needs of our business and customers.

• Lead the end-to-end product lifecycle for data products — from discovery and ideation through to delivery and iteration.
• Have some experience in AI/ML.
• Gather requirements and communicate with end users from a product perspective.
• Work in multidisciplinary teams, including data engineers, data scientists, analysts, and business stakeholders to define product requirements and success metrics.
• Develop and implement data standards to ensure consistency, accuracy, and interoperability across various systems and platforms.
• Design and validate data schemas, ensuring alignment with business logic, reporting needs, and downstream applications.
• Ensure data structures and models are optimized for scale, performance, and long-term maintainability.