Product Engineering Lead (Supply and R&D)

Mars Petcare UK; Greater London; On-site; GBP 70,000 - 100,000; Full time

Job summary

Mars Petcare UK is seeking a Product Engineering Lead to drive data-driven solutions within their Global Pet Nutrition division. The successful candidate will lead engineering teams to develop robust data solutions, enhance operational efficiency, and adhere to data governance. This leadership role demands a strategic vision and the ability to manage complex technical challenges.

Qualifications

• Expertise in Commercial/Procurement Analytics.
• Hands-on experience with big data technologies like Hadoop and Spark.
• Strong technical proficiency in SQL and NoSQL databases.

Responsibilities

• Lead data engineering efforts across product teams and establish best practices.
• Develop and maintain data pipelines supportive of analytics and machine learning.
• Drive adoption of DataOps principles for enhanced workflow efficiency.

Skills

Commercial/Procurement Analytics

Data Modeling

SQL

NoSQL Databases

Data Warehousing

Data Pipeline Development

ETL Processes

Big Data Technologies

Cloud Platforms

DataOps Practices

Education

Degree in Data Science, Computer Science, or related field

Tools

SAP (S/4 Hana)

Spark

Databricks

Hadoop

Kafka

AWS

Azure

Google Cloud

AWS Redshift

Azure Synapse Analytics

Google BigQuery

Job description

Product Engineering Lead (Supply and R&D)

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 places 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 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 core products.

Technical Leadership - Provide strong technical leadership to data engineers and DevOps 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.

DataOps Enablement and Optimization: Drive the adoption of modern DataOps 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 standards 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

• Expertise in Commercial/Procurement Analytics.
• Experience in SAP (S/4 Hana).
• Experience with Spark, Databricks, or similar data processing tools.
• Strong technical proficiency in data modeling, SQL, NoSQL databases, and data warehousing.
• Hands-on experience with data pipeline development, ETL processes, and big data technologies (e.g., Hadoop, Spark, Kafka).
• Proficiency in cloud platforms such as AWS, Azure, or Google Cloud and cloud-based data services (e.g., AWS Redshift, Azure Synapse Analytics, Google BigQuery).
• Experience with DataOps practices and tools, including CI/CD for data pipelines.
• Excellent leadership, communication, and interpersonal skills, with the ability to collaborate effectively with diverse teams and stakeholders.
• Strong analytical and problem-solving skills with a focus on driving actionable insights from complex data sets.

#LI-EN1

#TBDDT

Mars is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need assistance or an accommodation during the application process because of a disability, it is available upon request. The company is pleased to provide such assistance, and no applicant will be penalized as a result of such a request.

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Job Overview

ID:

1595194

Date Posted:

Posted 3 days ago

Expiration Date:

03/08/2025

Location:

Greater London

Competitive

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