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

at Nvidia
USD 184,000-287,500 per year
SENIOR
✅ On-site

Tech Stack

AI @ 4 API @ 4 BI @ 4 CI/CD @ 4 Communication @ 7 Data Engineering @ 4 Data Pipelines @ 4 Data Structures @ 4 Databricks @ 4 GenAI @ 4 Git @ 4 Machine Learning Observability Performance Optimization @ 4 Power BI @ 4 RAG @ 4 SQL @ 4 Security @ 4 Spark @ 4 Tableau @ 4

Details

Join NVIDIA's team of innovators to help advance SAP S/4HANA data capabilities, enterprise data products, and data governance. In this role, you will create reliable, governed data assets that support analytics, reporting, AI/ML, and self-service use cases.

Responsibilities

  • Compose, build, and maintain scalable Databricks pipelines using PySpark, SQL, Delta Lake, notebooks, and workflows, following reusable engineering patterns and performance guidelines.
  • Build SAP S/4HANA and ECC datasets across bronze, silver, and gold layers for finance, supply chain, procurement, order management, inventory, manufacturing, customer, supplier, and master data domains.
  • Convert SAP business processes into facts, dimensions, metrics, measures, and reusable semantic data assets.
  • Implement data quality, reconciliation, validation, lineage, observability, and production support measures.
  • Collaborate with SAP functional experts, business systems analysts, data architects, BI developers, and data scientists to understand source logic and deliver documented, trusted data products.
  • Use Unity Catalog and Immuta to manage catalogs, schemas, tables, views, permissions, tags, comments, lineage, ownership, row filters, masking, policy enforcement, and auditing.
  • Assess and apply SAP data extraction technologies, including CDS views, ODP/ODQ, SLT, SAP Datasphere, SAP BW extractors, BODS, APIs/OData, replication flows, and SAP Business Data Cloud.
  • Advise data engineers and analysts and produce reusable templates, patterns, and documentation to onboard new SAP domains and improve engineering maturity.

Requirements

  • 12 or more 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.
  • Hands-on experience with Databricks, Apache Spark/PySpark, SQL, Delta Lake, and production-level data pipelines.
  • Experience modeling and building curated datasets from SAP S/4HANA or SAP ECC, with knowledge of SAP data structures and extraction methods.
  • Knowledge of SAP business processes and data structures in areas such as finance, supply chain, procurement, sales, inventory, manufacturing, or master data.
  • Practical experience with Unity Catalog, including permissions, catalogs, schemas, tables, views, tags, comments, lineage, and data discovery in regulated environments.
  • Working knowledge of Immuta or similar governed data access platforms, including policy-based controls, masking, row-level security, user attributes, groups, and auditing.
  • Experience with data quality, reconciliation, testing, monitoring, and performance optimization for large-scale enterprise datasets.
  • Experience supporting other developers and improving engineering practices, code quality, and production readiness.
  • Strong interpersonal and communication skills for collaboration with technical teams and business stakeholders.

Preferred Qualifications

  • Experience with SAP Business Data Cloud, SAP Datasphere, SAP BW, SAP SLT, ODP/ODQ, CDS views, BODS, or SAP APIs/OData.
  • Experience 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-focused delivery.
  • Experience with Tableau, Power BI, Alteryx, Dataiku, or similar analytics and BI platforms.
  • Knowledge of CI/CD, Git, Databricks Asset Bundles or comparable workflow orchestration, automated deployment, data privacy, least-privilege access, sensitive data classification, and enterprise data governance.

Benefits

  • Equity and benefits are provided.
  • NVIDIA is committed to an inclusive work environment and is an equal opportunity employer.
  • Applications will be accepted at least until October 5, 2026.
  • NVIDIA uses AI tools in its recruiting processes.

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