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

Posted 6 Days Ago
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Santa Clara, CA, USA
In-Office
184K-288K Annually
Senior level
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
Design, build, and maintain scalable Databricks (PySpark/SQL/Delta Lake) pipelines to transform SAP S/4HANA and ECC data into curated, governed data products. Implement data quality, lineage, observability, and access controls (Unity Catalog, Immuta), collaborate with SAP experts and analytics teams, and mentor engineers to deliver production‑grade datasets for analytics and AI/ML.
Summary Generated by Built In

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.

What you’ll be doing:

  • 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.

What we need to see:

  • 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.

Ways to stand out from the crowd:

  • 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.

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, results-oriented and enjoy learning while having fun, then what are you waiting for? Apply today!

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 13, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Skills Required

  • 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 and building production-grade data pipelines.
  • Apache Spark / PySpark experience for ETL and scalable processing.
  • SQL experience for data modeling and transformation.
  • Delta Lake experience for data lakehouse architecture.
  • Proven experience modeling and building curated datasets from SAP S/4HANA or SAP ECC.
  • Deep understanding of SAP data structures, business processes, and extraction methods.
  • Hands-on experience with Unity Catalog for catalog, schema, table, view management and permissions.
  • Working knowledge of Immuta or similar governed data access platforms (policy controls, masking, row-level security).
  • Experience implementing data quality, reconciliation, validation, monitoring, and performance optimization for large enterprise datasets.
  • Demonstrated ability to mentor developers and improve engineering practices and production readiness.
  • Strong interpersonal and communication skills for collaboration with technical and business stakeholders.
  • Hands-on experience with SAP Business Data Cloud, SAP Datasphere, SAP BW, SLT, ODP/ODQ, CDS views, BODS, or SAP APIs/OData for advanced extraction/integration.
  • Track record preparing SAP datasets for AI/ML (feature engineering, forecasting, anomaly detection, GenAI/RAG).
  • Familiarity with semantic modeling, metric views, certified datasets, and business glossaries.
  • Experience with analytics and BI tools such as Tableau, Power BI, Alteryx, or Dataiku.
  • Strong foundation in CI/CD, Git, Databricks Asset Bundles or equivalent automated deployment and orchestration.
  • Experience with data privacy, least-privilege access, sensitive data classification, and enterprise data governance.

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”

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