SAP Platform and Technology Senior Manager

KPMG
Manchester
4 months ago
Applications closed

Related Jobs

View all jobs

Data Scientist - London

Data Engineer - London

Demand Planner

AI / Data Engineer

Business Development Manager (Staffing Solutions)

Business Development Manager (Staffing Solutions)

Job description

SAP Platform & Technology Senior Manager

 

We are seeking talented individuals with deep design and implementation experience in transforming our clients’ business towards a digital enterprise using SAP S4 HANA powered by BTP solutions. This is a high-profile role within the team, requiring strong client delivery skills, whilst supporting business development opportunities to grow the practice.

 

The successful candidate will be able to:

 

Evaluate and implement the right cloud services in SAP BTP to drive modern cloud-based solutions for our clients Plan and conduct workshops on identification of cloud service use cases including modern UI solutions Help clients plan their future Technology roadmap, architecture and landscape using user-centric technology led innovations Solve complex issues in Application Development & Integration using services like SAP Business Application Studio, SAP Build, SAP Integration Suite etc. Advice clients on intelligent technologies like Robotic Process automation, AI, Machine Learning solutions on SAP BTP Capable of supporting business development and sales initiatives including bid and proposal support in SAP Cloud Platform & Technology services

 

 

The Person

 

Demonstrable experience of having successfully delivered end-to-end SAP Cloud Transformation programmes within a Consulting environment Strong knowledge of S/4HANA configuration and best practices SAP system design, build and deployment experience – 3 full lifecycle implementations preferred Experience producing project deliverables (business requirements, functional specs, configuration document, process flows, use cases, requirements traceability matrices etc.) Detailed working knowledge of how processes are enabled within SAP Demonstrable experience in running and supporting pre-sales activities- RFPs, demos, client engagement Strong documentation, reporting and presentation skills Well-developed analytical skills and the ability to provide clarity to complex issues, and synthesize large amounts of information Strong interpersonal, team building, organisational and motivational skills Business analysis and requirements gathering abilities Experience of facilitating a design workshop and then translating the requirements into design Ability to build strong client relationships based on subject matter expertise and quality of delivery Ability to learn technology quickly through instruction Proven ability to collaborate and build strong relationships with varying team members Strong functional knowledge of at least one module Self-starter attitude and ability to work well within ambiguity

 

#LI-AP1

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.

Portfolio Projects That Get You Hired for AI Jobs (With Real GitHub Examples)

In the fast-evolving world of artificial intelligence (AI), an impressive portfolio of projects can act as your passport to landing a sought-after role. Even if you’ve aced interviews in the past, employers in AI and machine learning (ML) are increasingly asking candidates to demonstrate hands-on experience through the projects they’ve built and shared online. This is because practical ability often speaks volumes about your suitability for a role—far more than any exam or certification alone could. In this article, we’ll explore how to build an outstanding AI portfolio that catches the eye of recruiters and hiring managers, including: Why an AI portfolio is crucial for job seekers. How to choose AI projects that align with your target roles. Specific project ideas and real GitHub examples to help you stand out. Best practices for showcasing your work, from writing clear READMEs to using Jupyter notebooks effectively. Tips on structuring your GitHub so that employers can instantly see your value. Moreover, we’ll discuss how you can use your portfolio to connect with top employers in AI, with a handy link to our CV-upload page on Artificial Intelligence Jobs for when you’re ready to apply. By the end, you’ll have a clear roadmap to building a portfolio that will help secure interviews—and the AI job—of your dreams.

AI Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

In today's competitive AI job market, nailing a technical interview can be the difference between landing your dream role and getting lost in the crowd. Whether you're looking to break into machine learning, deep learning, NLP (Natural Language Processing), or data science, your problem-solving skills and system design expertise are certain to be put to the test. AI‑related job interviews typically involve a range of coding challenges, algorithmic puzzles, and system design questions. You’ll often be asked to delve into the principles of machine learning pipelines, discuss how to optimise large-scale systems, and demonstrate your coding proficiency in languages like Python, C++, or Java. Adequate preparation not only boosts your confidence but also reduces the likelihood of fumbling through unfamiliar territory. If you’re actively seeking positions at major tech companies or innovative AI start-ups, then check out www.artificialintelligencejobs.co.uk for some of the latest vacancies in the UK. Meanwhile, this blog post will guide you through 30 real coding & system-design questions you’re likely to encounter during your AI job interview. This list is designed to help you practise, anticipate typical question patterns, and stay ahead of the competition. By reading through each question and thinking about the possible approaches, you’ll sharpen your problem-solving skills, time management, and critical thinking. Each question covers fundamental concepts that employers regularly test, ensuring you’re well-equipped for success. Let’s dive right in.

Negotiating Your AI Job Offer: Equity, Bonuses & Perks Explained

Artificial intelligence (AI) has proven itself to be one of the most transformative forces in today’s business world. From smart chatbots in customer service to predictive analytics in finance, AI technologies are reshaping how organisations operate and innovate. As the demand for AI professionals grows, so does the complexity of compensation packages. If you’re a mid‑senior AI professional, you’ve likely seen job offers that include far more than just a base salary—think equity, bonuses, and a range of perks designed to entice you into joining or staying with a company. For many, the focus remains squarely on salary. While that’s understandable—after all, your monthly take‑home pay is what covers day-to-day expenses—limiting your negotiations to salary alone can leave considerable value on the table. From stock options in ambitious startups to sign‑on bonuses that ‘buy you out’ of your current contract, modern AI job offers often include elements that can significantly boost your long-term wealth and job satisfaction. This article aims to shed light on the full scope of AI compensation—specifically focusing on how equity, bonuses, and perks can enhance (or sometimes detract from) the overall value of your package. We’ll delve into how these elements work in practice, what to watch out for, and how to navigate the negotiation process effectively. Our goal is to provide mid‑senior AI professionals with the insights and tools to land a holistic compensation deal that accurately reflects their technical expertise, leadership potential, and strategic importance in this fast-moving field. Whether you’re eyeing a leadership role in machine learning at an established tech giant, or you’re considering a pioneering position at a disruptive AI startup, the knowledge in this guide will help you weigh the merits of base salary alongside the potential riches—and risks—of equity, bonuses, and other benefits. By the end, you’ll have a clearer sense of how to align your compensation with both your immediate lifestyle needs and long-term career aspirations.