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Senior AI Data Engineer - SAP-RPT Model Family

SAP

Canada · Hybrid Full-time Senior CA$108k – CA$223k/yr 4w ago

About the role

About SAP

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.


Summary

As a Senior Data & AI Engineer for the SAP‑RPT model family, you will build and scale the technical foundations that power our AI innovations. You will develop high‑quality, end‑to‑end data pipelines, execute complex data extractions, and engineer the high‑value datasets essential for our foundation model research and engineering teams.

Bridging the technical gap between raw enterprise data and advanced AI research, you will focus on tooling and pipelines for curating and refining data assets to ensure maximum utility and performance. While working hands‑on with cutting‑edge processing tools, you will ensure every dataset adheres to SAP’s unwavering commitment to industry‑leading compliance and data integrity. This is the ideal role for a highly technical, detail‑oriented individual eager to work at the core of data engineering and contribute to the development of one of the few world’s leading relational foundation models.


Responsibilities

  • Contribute to the development of the SAP‑RPT tabular foundation model family, helping shape next‑generation predictive capabilities for enterprise applications.
  • Design, build, and operate scalable tooling and data pipelines to ingest, process, and curate tabular data at enterprise scale.
  • Partner with stakeholders to identify, source, and define high‑impact predictive tabular use cases across SAP products and scenarios.
  • Extract, clean, validate, and enrich data with a strong focus on quality, consistency, and governance; prepare datasets for model training and benchmarking.
  • Collaborate closely with domain experts and application development teams (e.g., SAP S/4HANA) to interpret data, metadata, and development artifacts and translate them into ML‑ready signals.
  • Work hand‑in‑hand with data scientists and researchers, sharing data insights, constraints, and nuances to ensure models are effectively tailored to SAP enterprise data.
  • Perform deep‑dive data exploration to uncover patterns, edge cases, bias/leakage risks, and quality gaps that directly inform model development and evaluation.
  • Influence data architecture decisions to enable reliable, secure, and efficient data access for both training pipelines and production deployments.

Requirements

  • Education & Experience: PhD or Master’s degree in Computer Science, AI, or a related field, plus 5+ years of professional experience working with large‑scale, high‑performance data environments.
  • SAP Data & Domain Expertise: Proven proficiency in SAP S/4HANA, ABAP, and SAP GUI, with deep knowledge of relational business data and complex schemas. Must demonstrate a strong ability to navigate semantic models (VDM, CDS, OData) and apply enterprise‑grade business logic to key business objects and underlying table structures.
  • Data Engineering & SAP Ecosystem: Proven experience with high‑performance SQL databases and SAP’s data stack (e.g., BDC, HANA, BTP), including building and operating cloud‑native data pipelines. Strong Python skills; exposure to Knowledge Graphs is a plus (e.g., technologies like RDL).
  • Machine Learning: Solid foundation in machine learning with hands‑on Python development experience applying AI to real‑world problems—ideally in tabular/structured data settings.

Preferred Qualifications

  • Lead and support strategic data platform initiatives focused on scalable data enablement and value delivery within the SAP ecosystem.
  • Apply experience with Knowledge Graph technologies (e.g., RDF, SPARQL), metadata management systems, and/or ML‑centric data models.
  • Bring 5+ years of experience building and operating Python‑based ML/data pipelines, using technologies such as Databricks, Azure ML, Airflow, PySpark, Ray, and Azure Data Lake.
  • Contribute to Data Science / Machine Learning projects focused on tabular (structured) data, from data preparation through model development and deployment.

Meet Your Team

SAP is uniquely positioned to lead the next wave of AI by infusing intelligence directly into the business processes that run the world. Our team’s mission is to develop Foundation Models for structured data, starting with the launch and continued evolution of SAP‑RPT‑1. As the first generation of our relational model portfolio, SAP‑RPT‑1 represents our commitment to pioneering new research in a domain where SAP’s expertise in enterprise data structures provides an unmatched competitive edge. We are looking for innovators to join us in this journey to develop next‑generation models with even higher impact, bridging the gap between cutting‑edge AI research and the complex, structured reality of global enterprise data.


Why SAP

  • 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.

Inclusion & Belonging

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. 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.


Application Information

  • SAP is committed to Equal Employment Opportunity and provides accessibility accommodations to applicants with physical and/or mental disabilities. If you need accommodation or special assistance to navigate our website or complete your application, please email the Recruiting Operations Team at 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.
  • Qualified applicants will receive consideration for employment without regard to age, race, religion, national origin, ethnicity, gender (including pregnancy, childbirth, etc.), sexual orientation, gender identity or expression, protected veteran status, or disability, in compliance with applicable federal, state, and local legal requirements.

Compensation & Benefits

  • Targeted combined compensation range: CAD 108,100 – 222,800 (base salary + variable incentive). The actual offer will depend on education, skills, experience, scope of the role, location, and other factors determined through the selection process.
  • Variable incentive includes a targeted dollar amount; actual payout depends on company and personal performance.
  • A summary of benefits and eligibility requirements can be found at: www.SAPNorthAmericaBenefits.com.

Additional Requirements

  • Due to the global nature of the role and interactions with SAP entities and stakeholders in Canada, functional proficiency in English is required for positions based in Quebec.

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. Violations of these guidelines may result in disqualification from the hiring process.


Requisition ID: 448373 | Work Area: Software‑Design and Development | Expected Travel: 0 – 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI‑Hybrid

Requirements

  • PhD or Master’s degree in Computer Science, AI, or a related field, plus 5+ years of professional experience working with large-scale, high-performance data environments.
  • Proven proficiency in SAP S/4HANA, ABAP, and SAP GUI, with deep knowledge of relational business data and complex schemas.
  • Must demonstrate a strong ability to navigate semantic models (VDM, CDS, OData) and apply enterprise-grade business logic to key business objects and underlying table structures.
  • Proven experience with high-performance SQL databases and SAP’s data stack (e.g., BDC, HANA, BTP), including building and operating cloud-native data pipelines.
  • Strong Pythonskills; exposure to Knowledge Graphs is a plus (e.g., technologies like RDL).
  • Solid foundation in machine learning with hands-on Python development experience applying AI to real-world problems—ideally in tabular / structured data settings.

Responsibilities

  • Contribute to the development of the SAP-RPT tabular foundation model family, helping shape next-generation predictive capabilities for enterprise applications.
  • Design, build, and operate scalable tooling and data pipelines to ingest, process, and curate tabular data at enterprise scale.
  • Partner with stakeholders to identify, source, and define high-impact predictive tabular use cases across SAP products and scenarios.
  • Extract, clean, validate, and enrich data with a strong focus on quality, consistency, and governance; prepare datasets for model training and benchmarking.
  • Collaborate closely with domain experts and application development teams (e.g., SAP S/4HANA) to interpret data, metadata, and development artifacts and translate them into ML-ready signals.
  • Work hand-in-hand with data scientists and researchers, sharing data insights, constraints, and nuances to ensure models are effectively tailored to SAP enterprise data.
  • Perform deep-dive data exploration to uncover patterns, edge cases, bias/leakage risks, and quality gaps that directly inform model development and evaluation.
  • Influence data architecture decisions to enable reliable, secure, and efficient data access for both training pipelines and production deployments.

Benefits

health insurancedental insurancevision insurance

Skills

ABAPAIBTPBDCCDSData LakeDatabricksHANAKnowledge GraphsMLODataPythonPySparkRDLRDFRaySQLSAPSAP GUISAP S/4HANASPARQLVDMAzure ML

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