About the Role
As a key leader within the Office of the CTO at SAP, you will shape the future of our enterprise data, analytics, and AI ecosystem. This is a highly strategic, forward-looking role that sets the technical vision and architectural standards for our company's data infrastructure.
You will act as the connective tissue between data technologies and the enterprise reality. Specifically, you will serve as a advisor, and subject matter expert responsible for integrating the Apache Iceberg platform into SAP's Data & Analytics products. With a specialized focus on modern Data Lakehouse architectures, open table formats (Apache Iceberg), open catalog standards (Iceberg REST Catalog, Apache Polaris), and SAP's core data strategy (SAP HANA, Business Data Cloud, and SAP Analytics Cloud), you will ensure our data foundation is scalable, interoperable, and primed to support advanced analytics and next-generation AI initiatives.
Key Responsibilities
- Bridge Iceberg & SAP Data Products: Act as the primary Subject Matter Expert (SME) and strategic advisor for integrating Apache Iceberg open table formats into SAP's broader Data & Analytics portfolio. Ensure seamless, high-performance interoperability between open data lakehouse architectures and SAP products.
- Drive SAP's Data & AI Strategy: Define and own the architectural roadmap connecting modern Data Lakehouse paradigms with SAP's overarching data analytics strategy. Ensure architectural alignment across SAP HANA, Business Data Cloud (Datasphere), and SAP Analytics Cloud to support business intelligence, scalable machine learning, and Generative AI workloads.
- Champion Apache Iceberg: Serve as the foremost enterprise expert on Apache Iceberg. Design transition and federation strategies to create a unified, Iceberg-backed Lakehouse that extends the capabilities of SAP's core data engines for our customers.
- Design Open Catalog Architectures: Lead the evaluation, strategy, and implementation of interoperable metadata catalogs. Drive our adoption of the Iceberg REST catalog specification and Apache Polaris to ensure multi-engine compatibility (e.g., integrating SAP engines with Snowflake, Databricks, Dremio, Trino) and eliminate vendor lock-in.
- Navigate the Enterprise Landscape: Assess and integrate new technologies within a complex, highly regulated enterprise environment. Ensure all architectural decisions account for enterprise security, unified governance, RBAC, data lineage, and global compliance standards across the SAP ecosystem.
- Technical Evangelism & Guidance: Act as a trusted advisor to SAP engineering teams, product managers, and executive leadership. Author technical standards, architectural decision records (ADRs), and proof-of-concept (PoC) implementations to validate strategic bets.
- Vendor & Ecosystem Evaluation: Continuously monitor the rapidly evolving data and AI vendor landscape. Assess build-vs-buy scenarios, manage strategic technical partnerships, and ensure SAP remains at the forefront of the open-source data movement.
Qualifications
- Experience: 10+ years in data engineering, data architecture, or software engineering, with at least 3+ years in a strategic, enterprise-wide architectural role (OCTO or Enterprise Architecture experience is highly preferred).
- SAP Data Strategy Expertise (Nice to Have) : Detailed, hands-on knowledge of SAP's data and analytics strategy. Must have deep architectural experience with SAP HANA, Business Data Cloud (SAP Datasphere), and SAP Analytics Cloud.
- Deep Lakehouse Expertise: Extensive knowledge of Data Lakehouse paradigms and experience with major compute engines (Spark, Trino, Flink) and enterprise platforms. Expertise on Databricks and Snowflake are plus.
- Open Table Formats: Deep, hands-on, and theoretical understanding of Apache Iceberg (its internal mechanics, manifest files, snapshot isolation, and optimization techniques like compaction/Z-ordering).
- Catalog Mastery: Proven understanding of the metadata catalog ecosystem, specifically the Iceberg REST catalog API and emerging standards like Apache Polaris or Project Nessie.
- Enterprise AI/ML Context: Strong understanding of how data architecture impacts AI/ML pipelines, MLOps, vector databases, and LLM fine-tuning/RAG architectures.
- Enterprise Pragmatism: Experience dealing with the reality of enterprise landscapes-cloud networking, IAM integration, data privacy laws (GDPR/CCPA), and seamlessly connecting legacy on-premise systems to modern cloud architectures.
- Communication: Exceptional ability to translate complex technical concepts into business value for C-suite executives, while retaining the depth required to debate technical merits with senior engineers and product teams.
Requisition ID: 447786 | Work Area: Software-Design and Development | Expected Travel: 0 - 10% | Career Status: Professional | Employment Type: Regular Full Time | Additional Locations: #LI-Hybrid
Requisition ID: 447786
Posted Date: Jun 11, 2026
Work Area: Software-Design and Development
Career Status: Professional
Employment Type: Regular Full Time
Expected Travel: 0 - 10%
Location:
