Senior Data Engineer - SAP HANA Cloud & Graph

Accountabilities:: Design, build, and optimize data models on SAP HANA Cloud, including tables, calculation views, CDS artifacts, stored procedures, and SQLScript. Design and implement graph data models and traversal queries for connected-data use cases such as material substitution and compatibility, product and organizational hierarchies, and supply and fulfillment networks. Write and optimize high-performance SQL and SQLScript by analyzing execution plans, identifying bottlenecks, and implementing effective solutions. Lead performance engineering across the data layer, including partitioning, indexing, memory management, workload classes, and result caching. Build data ingestion and replication pipelines into HANA Cloud from SAP and non-SAP sources using technologies such as SDI, SDA, SLT, change data capture, or comparable approaches. Expose data to TypeScript-based product applications through secure, clean, and well-documented service layers. Establish and enforce standards for schema design, migrations, versioning, and database artifact code reviews. Implement database security and access controls, including roles and privileges, data masking, anonymization, and multi-tenant data isolation. Collaborate with machine learning and search engineers to ensure the data layer efficiently supports feature pipelines and search indexing. Own monitoring, alerting, backup and recovery processes, capacity planning, and readiness for HANA Cloud upgrades. Document relational, dimensional, and graph data models so other engineering teams can confidently build on the underlying data foundation. Requirements: Deep expertise in SAP HANA or HANA Cloud engineering, including data modeling, SQLScript, calculation views, and production performance tuning. Strong experience with graph database capabilities, including graph data modeling and traversal languages or technologies such as SAP HANA Graph, Cypher/Neo4j, Gremlin, or SPARQL. Sound technical judgment to determine when graph modeling provides meaningful advantages over traditional relational approaches. Expert-level SQL skills, including execution plan analysis and optimization of complex analytical and transactional queries. Experience designing and operating data replication and integration pipelines into HANA from enterprise source systems, with a practical understanding of how such pipelines can fail. Strong knowledge of relational and dimensional modeling, normalization trade-offs, and safe schema evolution. Proficiency in at least one application language, such as TypeScript, JavaScript, or Python, for developing services and data-layer tooling. Experience implementing database security and multi-tenant data isolation. Strong communication skills and a consistent approach to documenting data models and technical decisions for other engineers. Bachelor's degree in Computer Science, Information Systems, or a related technical field, or equivalent practical experience. Experience with SAP Business Technology Platform, including the Cloud Application Programming model and HDI containers, is preferred. Working knowledge of SAP SD and MM data structures and order-to-cash processes is a plus. Experience with the HANA Cloud vector engine, spatial engine, or machine learning libraries such as PAL/APL is advantageous. Experience with graph algorithms at scale, including pathfinding, centrality, community detection, or graph-based recommendation, is preferred. Knowledge graph, ontology, or RDF modeling experience is a plus. Experience supporting machine learning feature pipelines or search indexing from the data layer is advantageous. Experience with CI/CD for database artifacts, particularly HDI deployment pipelines, is preferred. Containerization and Kubernetes experience is a plus. SAP HANA certification is advantageous. Benefits: Fully remote working environment. Full-time contractor position. Opportunity to own a critical enterprise data layer built on SAP HANA Cloud. Hands-on work across relational databases, graph technologies, data integration, security, and performance engineering. Collaboration with machine learning, search, product, and engineering teams. Opportunity to work on complex connected-data use cases with significant enterprise impact. Exposure to modern SAP technologies, graph data modeling, and advanced data capabilities. Opportunity to establish technical standards for data architecture, security, reliability, and scalability.