Data Architect (Enterprise Data Foundations)

Mars
Slough
8 months ago
Applications closed

Related Jobs

View all jobs

Data Architect

Data Architect - Contract

Data Architect

Data Architect

Data Architect

Data & AI Solution Architect, Azure, Remote

JOB DESCRIPTION

Job Description:

Come become a part of a vibrant CDO team serving Mars Snacking Enterprise. Our team helps build the Data Platforms, Model & Engineer data products, craft Analytical products and Integrations to be a truly data driven growth engine. As we continue to expand and transform digitally, we’re actively seeking an experienced and skilled Data Architect to help model, build and own our Enterprise Data Foundations. This is a pivotal role that involves conceptualizing, designing and overseeing the implementation, and optimizing global data models to deliver value throughout the organisation. You’ll be designing and driving delivery of data products with a major focus on marketing, DCOM and overall Demand functions that will be the foundational pillars for data analytics solutions across diverse sources, internal and external that are high volume and varying complexity. You will draw on your experience and depth of knowledge to make use of modern tools and technologies always keeping business priorities at the forefront.

As our Data Architect, you’ll be tapping into your deep modelling expertise, business acumen and strategic vision to steer our data transformation strategy, aligning it with our business goals and objectives at both program and project levels. This role has a global reach, requiring you to coordinate and communicate with various internal teams within our Demand, Supply and Manufacturing domains.

What are we looking for?

Bachelor’s or master’s degree in computer science, Information Technology, or a related field. 10+ years of hands-on experience designing and implementing data architecture, modelling & integration solutions in complex enterprise environments using cloud technologies. Technical expertise and experience in databases and data engineering capabilities. Rich heritage in designing and building data models, data warehouses, analytics, and BI platforms, including experience with Big Data. Must know modern cloud platforms including Azure, GCP, etc and technologies across traditional and contemporary software, with focus as below:Expert understanding: Azure Data Factory, Databricks, Spark, Azure SQL Database, Azure DevOps/Git, Data Lake, Delta Lake/Lakehouse architecture, Power BI.Working Knowledge: Azure WebApp, Azure Networking concepts.Conceptual Knowhow (nice to have): Azure AI Services, ML concepts, Unity Catalog, Purview. Programming: SQL, Java, C#, C++, Python, R and visualization tools (PowerBI and React) Track record in building and developing successful data teams including mentoring junior staff. Ability to move fast and build prototypes to conduct proof-of-concepts exploring new areas. Proven experience as a Data Architect, with a focus on designing and implementing complex analytical solutions in a reputed organization. Excellent Communication and Story Telling skills to broad set of stakeholders across Business and technology. Knowledge on SAP and related systems is a great plus. Strong understanding of data governance and security considerations and best practices for data acquisition, including authentication, authorization, and data encryption. Leadership experience and the ability to influence and drive consensus among technical and non-technical teams.

What will be your key responsibilities?

Data architecture & Modelling:Lead the design of scalable data foundations and acquisition solutions, emphasizing scalability and performance.Data Acquisition and setup:Participate in technology discussions and recommendation of acquisition technologies, ensuring alignment with business needs of consistent and trusted data delivery.Collaboration and Communication:Work closely with cross-functional teams to translate business requirements into scalable data architectures. Partnering with different business domains of demand, supply, finance & Master data teams is crucial.Best Practices and Standards:Establish and enforce data architecture best practices, standards, and guidelines.Documentation:Create and maintain comprehensive documentation for data products and governance artefacts.Mentorship and Leadership:Mentor junior team members and collaborate with other architects to drive overall technology strategy.Evangelization:Ensure that project and program teams understand data product concept and know what they can expect out of it. Communicate integration value and capabilities. You will be expected to work on evangelization of data & integration with the ability to lead and influence across Developers to C-Suite.Stay on Trend:Lead with industry trends, emerging technologies, data and integration patterns to drive innovation within the organization.Project Planning:Participate in the estimation of project timelines, resources, and budgets related to integration efforts.

What can you expect from Mars?

Work with over 140,000 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

#LI-EN1

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.