National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Data Engineering Lead - Growth

myGwork
London
8 months ago
Applications closed

Related Jobs

View all jobs

Data Engineering Lead MLOps AI PaaS

AI Engineering Researcher

Senior Data Scientist - AD/ADAS

Engineering Lead I - Machine Learning Platform

Lead Data Scientist

- x3 Data Science Leads – Join a Leading Technology & Engineering Innovator - offices based in [...]

This job is with Mars, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter directly. 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 of Senior Director, Data Foundations, 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 across core and growth functions Key Responsibilities Please list the most important and relevant responsibilities Leadership and Team Management: Lead and mentor a team of data engineers and DevOps engineers. Provide guidance and support in the design, implementation, and maintenance of data assets. Foster a collaborative and high-performance team culture focused on innovation and excellence Data Asset Delivery : Drive the end-to-end delivery of data products. Collaborate closely with cross-functional teams to understand business requirements and translate them into technical solutions. Ensure timely and accurate delivery of data products that meet business needs and quality standards. DataOps and Optimization : Implement DataOps practices to streamline data engineering workflows and improve operational efficiency. Automate data pipeline deployment and monitoring using CI/CD tools. Technical Leadership: Provide technical leadership and guidance on data engineering best practices. Stay informed about industry trends and emerging technologies in data engineering and analytics. Standardization and Governance: Ensure adherence to data governance policies, procedures, and standards. Implement best practices for data management, security, and compliance. Promote data quality and integrity across all data products. Monitor data pipeline performance and optimize for scalability, reliability, and speed. 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. Job Specifications /Qualifications State the preferred education, knowledge, skills and experience this position requires. State the physical and/or mental requirements for the role (e.g. stand for x hours, lift x weight, concentration on repetitive tasks). Note: May differ from the current job holder's own skills and experience. Education & Professional Qualifications 8 years' experience as a Data Engineer. Knowledge / Experience 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. Experience with data visualization tools (e.g., PowerBI). Proficiency in Microsoft Azure cloud technologies would be a bonus. Key Mars Leadership Competencies (4-6) Refer to the Mars Talent and Development Library Note: competencies selected should be job related Communicates effectively Collaborates Drives Results Self-Development Key Functional Competencies & Technical Skills (3-5) Refer to the Mars Talent and Development Library Distinguish any preferred competences at the end of the list & notate them as "preferred" Data Modeling: Expertise in conceptual, logical, and physical data modeling, with an emphasis on designing scalable and efficient data structures. ETL Development: Proficiency in building and maintaining ETL processes, including data ingestion, transformation, and integration. Cloud Platforms: Proficiency in using cloud platforms like AWS, Azure, or Google Cloud for data storage, processing, and analytics. Database Management: Strong knowledge of both relational and non-relational database systems, including SQL and NoSQL databases. DataOps Practices: Experience with CI/CD for data pipelines and automating data engineering workflows to improve efficiency and reliability. Data Governance: Understanding of data governance principles, including data quality, metadata management, and regulatory compliance. 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.

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

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

Industry Insights

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

AI Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide – we refresh it every quarter so you always know who’s really scaling their artificial‑intelligence teams. Artificial intelligence hiring has roared back in 2025. The UK’s boosted National AI Strategy funding, record‑breaking private investment (£18.1 billion so far) & a fresh wave of generative‑AI product launches mean employers are jockeying for data scientists, ML engineers, MLOps specialists, AI product managers, prompt engineers & applied researchers. Below are 50 organisations that have advertised UK‑based AI vacancies in the past eight weeks or formally announced growth plans. They’re grouped into five easy‑scan categories so you can jump straight to the kind of employer – & culture – that suits you. For each company you’ll find: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, culture, mission) Use the internal links to browse current vacancies on ArtificialIntelligenceJobs.co.uk – or set up a free job alert so fresh roles land in your inbox.

Return-to-Work Pathways: Relaunch Your AI Career with Returnships, Flexible & Hybrid Roles

Stepping back into the workplace after a career break can feel like embarking on a whole new journey—especially in a cutting-edge field such as artificial intelligence (AI). For parents and carers, the challenge isn’t just refreshing your technical know-how but also securing a role that respects your family commitments. Fortunately, the UK’s tech sector now boasts a wealth of return-to-work programmes—from formal returnships to flexible and hybrid opportunities. These pathways are designed to bridge the gap, equipping you with refreshed skills, confidence and a supportive network. In this comprehensive guide, you’ll discover how to: Understand the booming demand for AI talent in the UK Leverage transferable skills honed during your break Overcome common re-entry challenges Build your AI skillset with targeted training Tap into returnship and re-entry programmes Find flexible, hybrid and full-time AI roles that suit your lifestyle Balance professional growth with caring responsibilities Master applications, interviews and networking Whether you’re returning after maternity leave, eldercare duties or another life chapter, this article will equip you with practical steps, resources and insider tips.

LinkedIn Profile Checklist for AI Jobs: 10 Tweaks That Triple Recruiter Views

In today’s fiercely competitive AI job market, simply having a LinkedIn profile isn’t enough. Recruiters and hiring managers routinely scout for top talent in machine learning, data science, natural language processing, computer vision and beyond—sometimes before roles are even posted. With hundreds of applicants vying for each role, you need a profile that’s optimised for search, speaks directly to AI-specific skills, and showcases measurable impact. By following this step-by-step LinkedIn for AI jobs checklist, you’ll make ten strategic tweaks that can triple recruiter views and position you as a leading AI professional. Whether you’re a fresh graduate aiming for your first AI position or a seasoned expert targeting a senior role, these actionable changes will ensure your profile stands out in feeds, search results and recruiter queues. Let’s dive in.