Senior Databricks Developer, SAP S/4 Data Products and Governance

NVIDIA•Us, CA

32d

About The Position

For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics. With our invention of the GPU - the engine of modern visual computing - the field has expanded to encompass personal computer games, movie production, product design, medical diagnosis and scientific research. Today, visual computing is becoming increasingly central to how people harmonize with technology, and there has never been a more exciting time to join our excellent team. NVIDIA is now passionate about innovation at the intersection of visual processing, high performance computing, and artificial intelligence. We are seeking a Senior Databricks Developer, SAP S/4 Data Products & Governance, to help build the future of AI/ML and Enterprise data products. You will turn complex SAP S/4HANA data into useful insights and promote innovation.

Requirements

12+ years of experience in data engineering, analytics engineering, BI engineering, or enterprise data platform development.
Bachelor’s or Master’s degree (or equivalent experience) in Information Systems, Computer Science, or Business.
Strong practical experience with Databricks, Apache Spark/PySpark, SQL, Delta Lake, and building production‑grade data pipelines.
Proven experience modeling and building curated datasets from SAP S/4HANA or SAP ECC, with solid knowledge of SAP data structures and extraction methods.
Deep understanding of SAP business processes and data frameworks in one or more areas such as finance, supply chain, procurement, sales, inventory, manufacturing, or master data.
Hands‑on experience with Unity Catalog for permissions, catalogs, schemas, tables, views, tags, comments, lineage, and data discovery in a governed environment.
Working knowledge of Immuta or similar governed data access platforms, including policy‑based controls, masking, row‑level security, user attributes, groups, and auditing.
Experience implementing data quality, reconciliation, testing, monitoring, and performance optimization for large‑scale, enterprise datasets.
Demonstrated ability to mentor other developers and improve the team’s engineering practices, code quality, and production readiness.
Strong interpersonal and communication skills for collaborating with both technical teams and business stakeholders.

Nice To Haves

Hands‑on experience with SAP Business Data Cloud, SAP Datasphere, SAP BW, SAP SLT, ODP/ODQ, CDS views, BODS, or SAP APIs/OData for advanced data integration and extraction.
Track record of preparing SAP datasets for AI/ML, forecasting, anomaly detection, feature engineering, GenAI/RAG, and self‑service analytics and dashboards.
Familiarity with semantic modeling, metric views, certified datasets, business glossaries, and data product–oriented delivery.
Experience with modern analytics and BI tools such as Tableau, Power BI, Alteryx, Dataiku, or similar platforms.
Strong foundation in CI/CD, Git, Databricks Asset Bundles (or equivalent workflow orchestration), automated deployment, data privacy, least‑privilege access, sensitive data classification, and enterprise data governance.

Responsibilities

Design, build, and maintain scalable Databricks pipelines using PySpark, SQL, Delta Lake, notebooks, and workflows, applying reusable engineering patterns and performance best practices.
Develop SAP S/4HANA and ECC datasets across bronze, silver, and gold layers, covering finance, supply chain, procurement, order management, inventory, manufacturing, customer, supplier, and master data domains.
Translate SAP business processes into trusted facts, dimensions, metrics, measures, and reusable semantic data assets that support analytics, reporting, AI/ML, and governed self‑service.
Implement robust data quality, reconciliation, validation, lineage, observability, and production support practices to ensure reliable, business‑ready datasets.
Work closely with SAP functional experts, business systems analysts, data architects, BI developers, and data scientists to understand source logic and deliver well‑documented, trusted data products.
Use Unity Catalog and Immuta to manage catalogs, schemas, tables, views, permissions, tags, comments, lineage, ownership, and fine‑grained access controls (row filters, masking, policy enforcement, auditing) in line with governance standards.
Assess and apply SAP data extraction technologies (CDS views, ODP/ODQ, SLT, SAP Datasphere, SAP BW extractors, BODS, APIs/OData, replication flows, SAP Business Data Cloud) to design efficient, reliable ingestion patterns.
Mentor data engineers and analysts, and build reusable templates, patterns, and documentation to onboard new SAP domains and raise the team’s overall engineering maturity.