SAP Technical Lead

Databricks•Mountain View, CA

8h•$198,200 - $272,600•Hybrid

About The Position

Databricks' IT organization is a product-led engineering team building intelligent, AI-powered platforms that simplify how work gets done across the company. For Finance, our vision is to eliminate manual, repetitive work by automating complex business processes, surfacing actionable insights, and orchestrating end-to-end workflows. We are reimagining finance operations so teams spend less time processing transactions, chasing approvals, and resolving exceptions, and more time delivering strategic insights that accelerate the business. We're looking for an SAP Technical Lead to own the technical architecture and delivery of our SAP platform. In this role, you'll define the technical vision for a clean-core S/4HANA landscape, lead the engineers who build on it, and architect the intelligent, agentic AI layer that sits between SAP and the Databricks Data Intelligence Platform. You'll set the standards, make the hard build-versus-adopt calls, and ensure everything we ship is secure, performant, and built to scale. SAP will serve as the foundation for Databricks' core finance processes, including Record-to-Report, Source-to-Pay, and Order-to-Cash. As the SAP Technical Lead, you will own how those processes are engineered—from the clean-core S/4HANA core and its extensions, to the integration fabric that connects SAP to the rest of the enterprise, to the AI and agentic services that make the experience intelligent. Rather than accumulating custom code inside the digital core, you'll champion a modern extensibility model on SAP BTP and the Databricks Lakehouse, so Finance teams get automated, AI-driven workflows on top of a core that stays clean, upgradable, and fast. Your mission is to combine the strength of SAP with the power of Databricks AI to build a technical foundation that lets the business scale.

Requirements

10+ years in SAP technical roles, with 3+ years as a technical lead or architect, and a proven track record delivering at least one full S/4HANA program (greenfield or conversion) plus BTP-based extension delivery.
Deep, hands-on command of clean-core principles—custom-code assessment and remediation, in-app vs. side-by-side extensibility, released APIs and extension points, and the governance that keeps the core clean over time.
Advanced experience across SAP BTP, ABAP Cloud and the ABAP RESTful Application Programming Model (RAP), CDS, and CAP, with Fiori/SAPUI5 on the front end.
Hands-on experience or strong technical command of agentic automation, LLM orchestration, retrieval-augmented generation, and evaluation—plus clear judgment about where AI belongs in a controlled, auditable ERP process and where it does not.
Advanced experience with SAP Integration Suite, API management, event-driven architecture, and REST/OData, integrating hybrid SAP and non-SAP landscapes.
Solid understanding of modern data platforms, SAP data extraction and modeling, pipelines, and semantic layers, and the practical work of making ERP data usable for analytics and AI.
Working knowledge of SAP authorizations, SoD, SOX and audit requirements, and the ability to architect solutions and automation that satisfy them.
Ability to translate business requirements into technical architecture, present tradeoffs to non-technical stakeholders, mentor engineers, and make pragmatic decisions that balance speed against long-term maintainability.

Nice To Haves

Experience building custom applications or automation layers on modern data platforms (such as Databricks) that extend or sit alongside SAP.
A clear point of view on build-versus-adopt tradeoffs across the SAP AI and extension stack (BTP, AI Core, Joule) versus a Databricks-native approach.
Hands-on knowledge of SAP integration surfaces and their limitations, including OData and REST APIs, CDS views, and Datasphere.
Experience running Agile delivery with system integrators and managed service partners, including vendor and SLA accountability.
SAP certification in SAP BTP, S/4HANA, or a relevant technology area, and prior work in a high-growth technology company where ERP had to scale quickly.

Responsibilities

Define and own the end-to-end technical architecture for the S/4HANA landscape (greenfield, brownfield, or selective data transition), aligned to clean-core principles, with clear guardrails that keep the digital core standard and upgrade-ready.
Define and own the extensibility strategy for SAP, using Databricks-native applications to address business requirements beyond core SAP capabilities. Establish clear architecture and governance standards to ensure extensions are scalable, secure, and aligned with the broader Finance technology strategy.
Drive a strong integration with ongoing Enterprise AI transformation within Databricks by bringing AI fluency and hands on AI experience.
Architect secure, resilient integration across SAP and non-SAP systems using SAP Integration Suite, event-driven patterns, APIs, OData v4, and change-data feeds into the Lakehouse, with clear contracts, error handling, and observability.
Partner with data engineering on the technical patterns for landing SAP data in Databricks—ingestion, CDC, semantic and master-data modeling, lineage, and governance.
Establish CI/CD, automated testing, and transport/deployment pipelines for BTP artifacts; own code and design reviews; and define the technical standards, security patterns, and best practices the team builds against.
Mentor developers and architects, lead technical steering, and act as the connective tissue across the SAP ecosystem (BTP, Integration Suite) and the systems around it, partnering closely with functional, product, and partner engineering teams.
Own performance, scalability, security, resilience, and cost across the landscape; report technical status, risks, and roadmaps to stakeholders.