Data Product Manager Hybrid – Build Reusable Data Platforms

LLOYD'S REGISTER INTERNATIONAL; Greater London, Saltaire, Glasgow; Hybrid; GBP 64,000 - 70,000; Full time

Job summary

Macmillan Cancer Support seeks a Data Product Manager to shape and deliver data products and capabilities. You will work across the technology organisation and with external partners to create reusable data products that enable better decision-making and personalised experiences for people affected by cancer.

You will own product visions, prioritise backlogs and collaborate with data engineers, analysts and architects to ensure data quality, governance and lifecycle management across datasets

Qualifications

• Experienced product manager with data products or data platforms.
• Curious, collaborative, able to explore complex problems and align diverse perspectives.
• Comfortable with data pipelines, modelling, APIs, integrations, metadata, lineage and access controls.
• Strong data product thinker focused on reusable data products and lifecycle ownership.
• Evidence and outcome focused, using data to prioritise work and demonstrate value.
• Experience delivering with agile and lean methodologies.

Responsibilities

• Own product visions and roadmaps for data products and capabilities.
• Collaborate with data engineers, architects and analysts to deliver reusable data products.
• Ensure data quality, privacy, security, governance, retention and responsible data use.

Skills

Data product management

Stakeholder collaboration

Data pipelines & APIs

Data governance & privacy

Agile/lean delivery

Data analysis and decision making

Communication & relationship building

Multidisciplinary teamwork

Tools

APIs

Job description

Macmillan Cancer Support seeks a Data Product Manager to shape and deliver data products and capabilities. You will work across the technology organisation and with external partners to create reusable data products that enable better decision-making and personalised experiences for people affected by cancer.

You will own product visions, prioritise backlogs and collaborate with data engineers, analysts and architects to ensure data quality, governance and lifecycle management across datasets