Data Engineer - AI and SAP Ecosystem

What you’ll do

• Build and scale the technical foundations that power our AI innovations.
• Develop high‑quality, end‑to‑end data pipelines, execute complex data extractions, and engineer high‑value datasets for foundation model research and engineering teams.
• Bridge the technical gap between raw enterprise data and advanced AI research, focusing on tooling and pipelines for curating and refining data assets.
• Ensure every dataset adheres to SAP’s commitment to compliance and data integrity.
• Contribute to the development of the SAP-RPT tabular foundation model family.
• 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.
• Extract, clean, validate, and enrich data with a focus on quality, consistency, and governance.
• Collaborate with domain experts and application development teams (e.g., SAP S/4HANA) to interpret data and translate it into ML‑ready signals.
• Work hand‑in‑hand with data scientists and researchers to tailor models to SAP enterprise data.
• Perform deep‑dive data exploration to uncover patterns, bias/leakage risks, and quality gaps.
• Influence data architecture decisions to enable reliable, secure, and efficient data access for training pipelines and production deployments.

Qualifications

• PhD or Master’s in Computer Science, AI, or related field, plus 5+ years of professional experience with large‑scale, high‑performance data environments.
• Proven proficiency in SAP S/4HANA, ABAP, SAP GUI, SAP data stack (BDC, HANA, BTP).
• Strong experience with high‑performance SQL databases.
• Python skills.
• Solid foundation in machine learning with hands‑on Python for real‑world problems, ideally on tabular data.

Preferred Qualifications

• Experience leading and supporting strategic data platform initiatives focused on scalable data enablement within the SAP ecosystem.
• Experience with Knowledge Graph technologies (RDF, SPARQL), metadata management systems, and/or ML‑centric data models.
• 5+ years building and operating Python‑based ML/data pipelines using Databricks, Azure ML, Airflow, PySpark, Ray, Azure Data Lake.
• Contribution to Data Science / Machine Learning projects focused on tabular data from preparation through deployment.

Benefits and Compensation

• Targeted combined compensation range: 108,100 – 222,800 CAD.
• Benefits and eligibility requirements can be found at www.SAPNorthAmericaBenefits.com.
• SAP is committed to the values of Equal Employment Opportunity and provides accessibility accommodations to applicants with physical or mental disabilities.
• Qualified applicants receive consideration without regard to age, race, religion, national origin, ethnicity, gender, sexual orientation, gender identity, veteran status or disability, in compliance with applicable federal, state, and local legal requirements.

Additional Qualifications

• Functional proficiency in English is required for positions based in Quebec.