PNE Data Foundations Sr. Lead

Mars IS UK
Windsor
4 days ago
Applications closed

Related Jobs

View all jobs

PNE Data Foundations Sr. Lead

Job Description:

The PNE Data Foundations Sr Lead ensures that Pet Nutrition Europe (PNE) has a strong, governed, and scalable data foundation to enable high-quality analytics and insights. This role is critical in bridging the gap between the AOE D&A data team and PNE, ensuring alignment with global data models, governance principles, and strategic data initiatives such as the DDF (Digital Data Foundation) program.

What are we looking for?

  • Preferred education Is a university degree In business or IT
  • Strong background in data engineering, data governance, and data architecture, ideally in a multinational or matrixed organization.

  • 5+ years of experience in data engineering, analytics, or data management, with hands-on expertise in cloud-based data platforms (e.g., Azure, AWS, GCP, Snowflake).

  • Proven expertise in designing, developing, and maintaining scalable data pipelines, ETL/ELT processes, and integrations to support advanced analytics.

  • Experience with data governance frameworks, master data management (MDM), metadata management, and ensuring data compliance with global standards.

  • Deep understanding of SQL, Python, Spark, or other relevant data processing technologies used for data transformation and analytics enablement.

  • Familiarity with modern data architectures, including data lakes, data warehouses, and data mesh principles.

  • Experience working with global and regional teams to align on data strategy, governance, and best practices.

  • Strong knowledge of data quality frameworks and best practices for ensuring high integrity, reliability, and consistency of data assets.

What will be your key responsibilities?

  • Data Governance & Compliance:Ensure all PNE data assets follow the governance frameworks, data quality standards, and security policies defined by the AOE D&A data team.

  • Data Model & Architecture Alignment:Ensure that analytics solutions within PNE fully leverage the data models, governance structures, and best practices established at the AOE level.

  • Data Engineering & Infrastructure:Oversee the design, development, and maintenance of data pipelines, integrations, and ETL processes to ensure efficient data flow and accessibility for analytics use cases.

  • Collaboration & Stakeholder Management:Act as the key connection between AOE D&A and PNE, facilitating knowledge-sharing, alignment, and implementation of strategic data initiatives, including the DDF program.

  • Data Platform Optimization:Work closely with AOE data teams and PNE analytics teams to optimize the data infrastructure, ensuring performance, scalability, and cost efficiency.

  • Metadata & Asset Management:Drive consistent metadata management and data asset governance, ensuring data reliability, accessibility, and standardization across PNE.

  • Enablement & Best Practices:Educate and support the PNE teams in data stewardship best practices, ensuring they effectively leverage governed data assets and self-service capabilities.

  • Monitoring & Data Quality Assurance:Implement data validation, lineage tracking, and anomaly detection mechanisms to ensure high data quality across PNE analytics initiatives.

What can you expect from Mars?

  • Work with diverse and talented Associates, all guided by the Five Principles.
  • Join a purpose driven company, where we’re striving to build the world we want tomorrow, today.
  • Best-in-class learning and development support from day one, including access to our in-house Mars University.
  • An industry competitive salary and benefits package, including company bonus.

#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.

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Machine‑Learning Jobs for Non‑Technical Professionals: Where Do You Fit In?

The Model Needs More Than Math When ChatGPT went viral and London start‑ups raised seed rounds around “foundation models,” many professionals asked, “Do I need to learn PyTorch to work in machine learning?” The answer is no. According to the Turing Institute’s UK ML Industry Survey 2024, 39 % of advertised ML roles focus on strategy, compliance, product or operations rather than writing code. As models move from proof‑of‑concept to production, demand surges for specialists who translate algorithms into business value, manage risk and drive adoption. This guide reveals the fastest‑growing non‑coding ML roles, the transferable skills you may already have, real transition stories and a 90‑day action plan—no gradient descent necessary.

Quantexa Machine‑Learning Jobs in 2025: Your Complete UK Guide to Joining the Decision‑Intelligence Revolution

Money‑laundering rings, sanctioned entities, synthetic identities—complex risks hide in plain sight inside data. Quantexa, a London‑born scale‑up now valued at US $2.2 bn (Series F, August 2024), solves that problem with contextual decision‑intelligence (DI): graph analytics, entity resolution and machine learning stitched into a single platform. Banks, insurers, telecoms and governments from HSBC to HMRC use Quantexa to spot fraud, combat financial crime and optimise customer engagement. With the launch of Quantexa AI Studio in February 2025—bringing generative AI co‑pilots and large‑scale Graph Neural Networks (GNNs) to the platform—the company is hiring at record pace. The Quantexa careers portal lists 450+ open roles worldwide, over 220 in the UK across data science, software engineering, ML Ops and client delivery. Whether you are a graduate data scientist fluent in Python, a Scala veteran who loves Spark or a solutions architect who can turn messy data into knowledge graphs, this guide explains how to land a Quantexa machine‑learning job in 2025.

Machine Learning vs. Deep Learning vs. MLOps Jobs: Which Path Should You Choose?

Machine Learning (ML) continues to transform how businesses operate, from personalised product recommendations to automated fraud detection. As ML adoption accelerates in nearly every industry—finance, healthcare, retail, automotive, and beyond—the demand for professionals with specialised ML skills is surging. Yet as you browse Machine Learning jobs on www.machinelearningjobs.co.uk, you may encounter multiple sub-disciplines, such as Deep Learning and MLOps. Each of these fields offers unique challenges, requires a distinct skill set, and can lead to a rewarding career path. So how do Machine Learning, Deep Learning, and MLOps differ? And which area best aligns with your talents and aspirations? This comprehensive guide will define each field, highlight overlaps and differences, discuss salary ranges and typical responsibilities, and explore real-world examples. By the end, you’ll have a clearer vision of which career track suits you—whether you prefer building foundational ML models, pushing the boundaries of neural network performance, or orchestrating robust ML pipelines at scale.