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Title : Product Engineer Lead; Demand

Job in Greater London, London, Greater London, EC1A, England, UK
Listing for: Mars, Incorporated and its Affiliates
Full Time position
Listed on 2026-01-16
Job specializations:
  • IT/Tech
    Data Engineer, Data Science Manager
Salary/Wage Range or Industry Benchmark: 100000 - 125000 GBP Yearly GBP 100000.00 125000.00 YEAR
Job Description & How to Apply Below
Position: Title : Product Engineer Lead (Demand)
Location: Greater London

Job Description

Are you passionate about Data and Analytics (D&A) and excited about how it can completely transform the way an enterprise works? Do you have the strategic vision, technical expertise, and leadership skills to drive data-driven solutions? Do you want to work in a dynamic, fast-growing category? If so, you might be the ideal candidate for the role in the Data and Analytics function for Global Pet Nutrition (PN) at Mars.

Pet Nutrition (PN) is the most vibrant category in the FMCG sector. As we work to transform this exciting category, a new program, Digital First, has been mobilized by the Mars Pet Nutrition (PN) leadership team. Digital First placesПК pet parents at the center of all we do in Mars PN, while digitalizing a wide range of business process areas, and creating future fit capabilities to achieve ambitious targets in top line growth, earnings, and pet parent centricity.

The Digital First agenda requires Digitizing at scale and requires you to demonstrate significant thought leadership, quality decision making, deep technical know‑how, and an ability to navigate complex business challenges while building and leading a team of world‑class data and analytics leaders.

With Digital First, PN is moving to a Product based model to create business‑facing digital capabilities. Develop and maintain robust data pipelines and storage antibacterial solutions to support data analytics and machine‑learning initiatives. Reporting to the Director‑Data engineering solution, The role operates globally in collaboration with teams engineering teams across growth products.

Technical Leadership - Provide strong technical leadership to data engineers and Dev Ops engineers across growth product teams. Act as a thought partner in the design, implementation, and evolution of scalable data platforms and assets. Champion best practices in data engineering and foster a collaborative, innovative, and high‑performance culture across teams.

Engineering Standards and Frameworks: Define, maintain, and evolve data engineering standards, patterns, and frameworks that product teams can adopt. Ensure consistency, quality, and reusability across solutions. Serve as a point of accountability for technical decisions and architectural direction, while empowering product teams to execute effectively.

Data Ops Enablement and Optimization: Drive the adoption of modern Data Ops principles to streamline engineering workflows. Partner with platform teams to establish CI/CD pipelines, observability standards that improve operational efficiency, reliability, and speed across data pipelines.

Data Governance and Quality Assurance: Embed governance, security, and data quality practices into engineering workflows. Define guardrails and reference implementations for data access control, data lineage, and compliance. Promote consistent metadata management and enforce technical standardsרי to ensure trust in data assets.

Stakeholder Engagement: Collaborate with PN D&A leadership, PN product owners, and segment D&A leadership to synchronize and formulate data priorities aimed at maximizing value through data utilization.

Knowledge / Experience
  • Data Engineering Leadership Milwaukee : Ability to lead global technical teams in building scalable data platforms, data pipelines, and infrastructure that support advanced analytics and machine learning.

  • Data Ops & Dev Ops Enablement: Skilled in implementing CI/CD pipelines, observability standards, and modern engineering workflows to enhance pipeline reliability, agility, and operational efficiency.

  • Technical Standards & Frameworks: Experience in defining and enforcing data engineering best practices, architectural patterns, and reusable frameworks across multiple product teams.

  • Strong capability in embedding governance, data lineage, access control, and compliance requirements into engineering processes to ensure data integrity and trust.

  • Digital Analytics Expertise: Deep understanding of digital data sources and analytics tools related to customer journeys, digital engagement, and business performance measurement.

  • Strategic Revenue Management (SRM): Familiarity with using data to support…

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