Synced from SAP SuccessFactors · Jul 5

Data Engineer

SAPGarching bei München (Munich), DE, 85748Posted Jul 5, 2026
Data EngineerSenior
Apply with one profileSave & get alerts

Mirrored from SAP's own SAP SuccessFactors careers system · refreshed hourly

1,011
Other open SAP roles
Jul 5
Posted
SAP SuccessFactors
Applicant system
Job descriptionReq 1401962933

We help the world run better
At SAP, we keep it simple: you bring your best to us, and we'll bring out the best in you. We're builders touching over 20 industries and 80% of global commerce, and we need your unique talents to help shape what's next. The work is challenging – but it matters. You'll find a place where you can be yourself, prioritize your wellbeing, and truly belong. What's in it for you? Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed. 

 


What you`ll do

At SAP, we're integrating state-of-the-art AI technology with our industry-specific data and deep process knowledge to innovate across SAP products & services. Agentic AI based on Large Language Models (LLMs) is transforming how users interact with their business applications. Still, the understanding of structured and unstructured business data such as business data models, business process metadata and documentation is limited in pre-trained LLMs, challenging using agents at scale and for complex tasks. It is SAP's mission to overcome this challenge within the realm of Business AI. Our goal is to provide Knowledge Graphs (KGs) as key differentiators to address LLM challenges like hallucination and compliance, as well as enable the development of the foundation models on structured data to deliver distinctive generative AI solutions to our customers.  

The Role
•    Unique opportunity to build the data foundation for SAP’s Knowledge Graphs – the source of explicit knowledge across multiple SAP domains.
•    Design and build robust data pipelines that ingest, transform, and load structured and unstructured business data (including SAP data) into RDF Knowledge Graphs at scale.
•    Map source data into ontologies and SHACL schemas, develop SPARQL-based transformations, and operate triple stores in production alongside Knowledge and Data engineering teams and stakeholders.
•    Collaborate closely with domain specialists and data owners to understand source systems (SAP and non-SAP) and translate their requirements into reliable Knowledge Graph data flows and provisioning.
•    Make critical design decisions on the data engineering stack – triple stores, ETL/ELT tooling, orchestration, and integration with downstream Generative AI applications. 
•    Contribute to thought leadership at the intersection of Data Engineering, Knowledge Graphs, and Generative AI. 
•    Present, discuss, and explain how high-quality Knowledge Graph data can benefit business use cases, and proactively propose new cases to relevant stakeholders.

 

What you bring
•    PhD or Master’s degree in computer science, artificial intelligence, physics, mathematics or other relevant disciplines
•    2+ years of related professional experience with a strong background in Data Engineering, ideally including working with Knowledge Graphs in a business context
•    Experience designing and operating large-scale data pipelines (batch and streaming) using modern data engineering tooling
•    Important: Good knowledge of SAP data and SAP applications – their data models and business objects. Not just the extraction interfaces but down to table level.
•    Experience mapping business operations and source systems into clear data models, ontologies, and organized schemas.
•    Awareness of latest trends at the intersection of Data Engineering, Knowledge Graphs, and LLMs – e.g. KG construction from unstructured data, graph RAG, KG embeddings.
•    Solid command of SQL, modern data warehousing/lakehouse concepts, and cloud data platforms (e.g., AWS, GCP, Azure, Databricks).
•    Experience in Data Engineering with a hands-on approach to solving data challenges.
•    Fluent in Python and the ability to convert your ideas into productive code. 
•    Working proficiency in the RDF Knowledge Graph technology stack (RDF, RDFS, OWL, SHACL, SPARQL) and hands-on experience operating triple stores - familiarity with property graph solutions (e.g., Neo4j) is a strong plus - otherwise willingness and ability to learn and skill up in this area rapidly is required. 
•    Working knowledge of the current triple store ecosystem (commercial and open-source, e.g., GraphDB, Stardog, Virtuoso, Apache Jena, Blazegraph) and Enterprise Knowledge Graph architectures is a plus

•    Ability to advise diverse stakeholders on how to bring their data into an enterprise Knowledge Graph and apply it to business use cases. 
•    Strong communication and collaboration skills, with the ability to work effectively in cross-cultural teams. 
 

Meet your team

SAP's AI organization is dedicated to seamlessly infusing AI into all enterprise applications, enabling customers, partners, and developers to enhance business processes and generate remarkable business value. Join our international AI team where innovation thrives, opportunities for personal development abound, and exceptional colleagues collaborate globally. 
 
#SAPBusinessAICareers #LI-KH1

Bring out your best
SAP innovations help more than four hundred thousand customers worldwide work together more efficiently and use business insight more effectively. Originally known for leadership in enterprise resource planning (ERP) software, SAP has evolved to become a market leader in end-to-end business application software and related services for database, analytics, intelligent technologies, and experience management. As a cloud company with two hundred million users and more than one hundred thousand employees worldwide, we are purpose-driven and future-focused, with a highly collaborative team ethic and commitment to personal development. Whether connecting global industries, people, or platforms, we help ensure every challenge gets the solution it deserves. At SAP, you can bring out your best.  

We win with inclusion
SAP’s culture of inclusion, focus on health and well-being, and flexible working models help ensure that everyone – regardless of background – feels included and can run at their best. At SAP, we believe we are made stronger by the unique capabilities and qualities that each person brings to our company, and we invest in our employees to inspire confidence and help everyone realize their full potential. We ultimately believe in unleashing all talent and creating a better world.

SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you are interested in applying for employment with SAP and are in need of accommodation or special assistance to navigate our website or to complete your application, please send an e-mail with your request to Recruiting Operations Team: Careers@sap.com.

For SAP employees: Only permanent roles are eligible for the
SAP Employee Referral Program, according to the eligibility rules set in the SAP Referral Policy. Specific conditions may apply for roles in Vocational Training.

AI Usage in the Recruitment Process

For information on the responsible use of AI in our recruitment process, please refer to our Guidelines for Ethical Usage of AI in the Recruiting Process.

Please note that any violation of these guidelines may result in disqualification from the hiring process.

Requisition ID: 442515  | Work Area: Software-Design and Development  | Expected Travel: 0 - 10%  | Career Status: Professional  | Employment Type: Regular Full Time   | Additional Locations:  #LI-Hybrid

View original posting on SAP SuccessFactors

What applying to SAP usually looks like

Based on publicly available information, candidates applying through successfactors typically begin by submitting an online profile and resume through SAP's careers portal, which commonly integrates with successfactors for application tracking and status updates. Applicants may receive automated confirmation emails and periodic status changes visible within the candidate portal. The process can generally include an initial recruiter screening, followed by hiring manager conversations and may include multiple stages such as technical or role-specific assessments depending on the position. Some roles may involve panel discussions or skills evaluations. Communication is often handled through the platform itself, though candidates may also be contacted by phone or email. Response times vary, and candidates are encouraged to monitor their application dashboard and email regularly. Preparing role-relevant examples and reviewing the job description closely is generally advisable.”

Based on publicly available information. LandEarly does not verify interview process details.

Land this one early - before the req fills.

LandEarly tailors your resume and screening answers to each posting, submits within minutes of a role going live, and tracks every application in one place.

Free to start · No credit card · Cancel anytime

Keep exploring

What this role pays, where else it is open, and how to write the application.

Data Engineer
SAP · Garching bei München (Munich), DE, 85748
Apply