Senior AI Data Engineer - SAP-RPT Model Family

SAP • Montreal, QC

4d • Hybrid

About The Position

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.

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.
• 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 Python skills.
• Solid foundation in machine learning with hands-on Python development experience applying AI to real-world problems—ideally in tabular / structured data settings.

Nice To Haves

• 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.
• Exposure to Knowledge Graphs is a plus (e.g., technologies like RDL).

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

• Constant learning, skill growth, great benefits, and a team that wants you to grow and succeed.
• A summary of benefits and eligibility requirements can be found by clicking this link: www.SAPNorthAmericaBenefits.com.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree