Manager SAP AI & Data Engineering

KPMG N.V.
Amstelveen, Netherlands
3 days ago
Apply on www.werkenbijkpmg.nl
Prepare application

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Compensation
€6,250.0
Working hours
Regular working hours
Languages
Dutch, English

Tech stack

Artificial Intelligence Encodings Information Systems Information Technology Consulting Data Architecture Information Engineering Software Maintenance SAP (Applications) SAP Business Suiteing SAP Implementation Software Engineering Information Technology
+1 more
Data Management

Job description

You will be part of a growing SAP AI team and work closely with colleagues across SAP, data, platforms, and technology consulting. You will:

  • Lead client engagements and workstreams focused on AI-enabled transformation, data platforms, and software product delivery.
  • Own the technical direction of solutions, review designs and implementation choices, and ensure alignment with enterprise architecture and quality standards.
  • Structure delivery teams, coordinate dependencies, and maintain control over scope, planning, risks, quality, and outcomes.
  • Work with clients to identify high-value AI use cases and convert them into scalable solutions integrated with SAP and the wider technology landscape.
  • Support workshops, proposals, and client conversations with a strong point of view on AI, data, architecture, and engineering.
  • Coach consultants and technical specialists, build reusable knowledge, and contribute to the growth of KPMG’s AI-enabled SAP proposition.
  • Stay current on developments in AI engineering and SAP Business AI, and translate relevant innovations into practical client value., As a Manager SAP AI & Data Engineering, you will lead complex AI and data initiatives from concept through implementation and operations. You will safeguard architectural quality, scalability, and maintainability, while connecting AI engineering with ERP-driven business transformation. You will focus on:
  • Leading complex AI and data programs across the full delivery lifecycle, from design and planning to implementation, adoption, and continuous improvement.
  • Driving the evolution and technical advancement of our SAP Business AI landscape to enable and deliver scalable and innovative solutions for clients.
  • Defining solution architectures and technical standards for secure, scalable, and maintainable AI-enabled products.
  • Translating business and transformation requirements into pragmatic technical roadmaps, product backlogs, and delivery plans.
  • Guiding the design, build, deployment, and maintenance of software products and services, as well as reusable AI accelerators.
  • Embedding AI into SAP transformation programs and connecting SAP capabilities with broader data, cloud, and enterprise architectures.
  • Managing multidisciplinary teams and aligning stakeholders across business, technology, architecture, security, and delivery.
  • Driving engineering quality through sound governance, testing, monitoring, documentation, and responsible AI practices.

Requirements

  • A completed university Master’s degree, preferably in computer science, data science, artificial intelligence, software engineering, information systems, or a related field.
  • Proven experience in managing complex AI, data, analytics, or software delivery programs in a consulting or enterprise environment.
  • Strong experience in designing, building, deploying, and maintaining software products and services, including architectural decision-making and lifecycle ownership.
  • Solid understanding of modern AI and data architectures, software engineering practices, integration patterns, cloud platforms, and operational considerations.
  • Experience with ERP systems and large-scale transformation programs, with specific knowledge of SAP environments and implementation contexts.
  • Affinity with, and practical exposure to, SAP’s AI proposition and the application of AI within SAP-enabled business processes.
  • Ability to lead technical teams, coach colleagues, manage delivery risks, and communicate complex topics clearly to senior client stakeholders.
  • A hands-on, outcome-oriented mindset, combined with commercial awareness and the ability to identify and shape new opportunities.
  • Proficiency in English; knowledge of Dutch is an advantage.

Benefits & conditions

  • Gross salary between € 5.100 and € 6,250 per month depending on your work experience, variable performance based reward, a fixed expense allowance and a fixed working from home allowance per working day.
  • 30 vacation days (on a full-time basis) and the option to buy more days or sell your vacation days.
  • At KPMG we work hybrid, so you can work from home or at the office.
  • A completely furnished home office.
  • A lease car or a mobility budget.
  • A laptop and iPhone.
  • Choice to pick from different courses which contribute to your own personal and professional development.
  • Diversity networks in the areas of pride, gender, ability, cultural diversity, and generations that regularly organize various activities to celebrate differences!
  • Focus on well-being! There is a gym at the Amstelveen office or you can get a discount for a gym near your house and you get access to different health and/or vitality programs.
  • ‘Together’ is one of our core values. So you can count on different social activities, like team events, drinks with colleagues and events with all your KPMG colleagues., Have you applied? Then you will receive an invitation for the KPMG Talent Pitch immediately after your application. In the Talent Pitch, we not only get to know you, but you also get to know us better. We will also give you a tour of the world of KPMG. During the pitch, you will complete a personality questionnaire and take an aptitude test. Step 2. The first interview

After completing the KPMG Talent Pitch, we will invite you for a first interview with a recruiter. In some cases, a colleague from the relevant department will also be present at the interview. This interview is a mutual introduction, where you also get the chance to ask all the questions you probably have. Step 3. Follow-up interview

Did you have a positive conversation and are you still enthusiastic? If we also see a match, a second meeting will follow. In this second interview, we will delve deeper into the role and the substantive themes you will be dealing with. You may be asked to prepare a business case for the interview. Sometimes there is a final interview. Step 4. Offer

Is there a match? Then we will make you an offer and hopefully you will start at KPMG soon. The offer will not only include your salary but also all our employment conditions, such as your pension, vacation days, and more! Do you agree with our offer? Then we congratulate you as our new colleague and take the last step. Step 5. Screening

We want to be an integral and reliable organization in all respects, so we screen everyone who comes to work with us. DISA conducts this screening and checks references, among other things. Everything in order? The path to a great career at KPMG is open to you. You will then start with the onboarding program.

Would you like to know more about our application procedure? Then contact HR Recruitment via recruitment@kpmg.nl.

  • Step 1
  • Step 2
  • Step 3
  • Step 4
  • Step 5

Apply for this position

This job is hosted externally. Click below to view the full posting and apply.

Apply on www.werkenbijkpmg.nl
Prepare application

Good distractions

Talks and stories from around this role — technically off-topic, practically not.

3:17 min

Optimizing character encoding with Kim variable byte encoding

Douglas Crockford Douglas Crockford · World Congress 2024

3:43 min

Data management for stateful cloud-native workloads

Michael Cade · World Congress 2022

8:43 min

Extrapolating data collection methods and cloud architecture data pipelines

Becky Gandillon · LIVE

1:26 min

Establishing the first chief data officer role at SAP

Katrin Lehmann Katrin Lehmann +1 · Coffee With Developers

2:18 min

Core principles of decentralized data mesh architecture

Olga Woschitz Olga Woschitz +1 · Europe 2026 Virtual

4:12 min

Distilling cross-encoder models into smaller efficient sentence embedding models

Marek Suppa · LIVE

Videos

See all

Related articles

See all