Our cross-functional Engineering teams develop scalable and secure microservices and APIs for the different domains of our product. Our DevX (Developer Experience) tribe is dedicated to empowering these teams with the best tools, platforms, and processes. Within DevX, the Product Analytics team's mission is to provide and operate a world-class data platform. We enable development teams and product managers to draw insights from product data, make data-informed decisions on new features, and evaluate the performance of their products in the real world. As a Staff Platform Engineer for Databricks & DataOps, you are the cornerstone of our data platform. You are not only a senior individual contributor but also a technical leader who will take ownership of our entire global data analytics infrastructure. With a strong customer-centric mindset, you will enable hundreds of internal users to leverage data effortlessly and securely. You will be the primary driver of our DataOps practice, ensuring our platform is scalable, reliable, cost-efficient, and secure across the globe. WHY SHOULD YOU CARE? Well, there are multiple reasons: We're on a strong growth trajectory in terms of ARR and team size while scaling in a sustainable and profitable way, making us successful in even challenging economical phases. Our products are industry-leading with happy customers and a NPS of 60. Our culture of empowered product teams means we solve problems instead of implementing features. We drive our efforts through close contact with our customers and measuring how they use our products. We build it, we run it. We ensure customers can rely on resilient and performant products. We stay ahead of trouble through a high degree of automation, alerting, SRE practises and On-Call. There is no dedicated operations department in place at SAP LeanIX. We prioritize continuous improvement, collaboration and knowledge sharing. We constantly iterate on our engineering practices and skills to build a software architecture that supports fun at work and long term success of the business. We value open access to leadership, transparency and personal development. We successfully enabled many software engineers to grow along with the company into engineering manager or technical lead positions. You’ll continue this success story while we offer you opportunities to grow. We value a healthy life balance and our employees make room for interests and relations outside of their job. We offer a hybrid working environment, providing a high grade of flexibility while meeting colleagues in one of our offices from time to time. WHAT IS WAITING FOR YOU? As the technical lead for our data platform, you will play an important role in building a self-service, automated, and robust ecosystem for product data analytics. Architect and Own Our Global Databricks Platform: You will design, build, and maintain our entire Azure Databricks environment across 10 global regions using Terraform. This includes architecting the compute and runtime environment with dbt as the core component for data transformations in our product analytics pipelines. Champion a "DataOps" Culture: You will implement and evangelize DataOps principles, creating automated, repeatable, and reliable processes for managing data, infrastructure, and analytics workflows. Implement and maintain a federated Data Architecture: You will be a key player in our transition to a data mesh. You will architect and implement the technical aspects of our data platform in Databricks, enabling domain teams to own their data products while maintaining central governance and discoverability through Unity Catalog. Drive Governance and Security: You will establish and enforce best practices for data governance, security, and compliance. Optimize for Performance and Cost: With a data engineering mindset, you will proactively monitor and tune Spark jobs, define optimal cluster policies, implement cost-management strategies (e.g., spot instances, autoscaling), and guide teams on writing efficient queries and data transformations. Empower Your Customers: You will create frictionless onboarding paths and self-service capabilities for data engineers, analysts, and data scientists, acting as the subject matter expert and go-to person for all things Databricks. This includes providing self-service frameworks for creating and deploying new dbt projects and acting as the go-to expert for running dbt efficiently on Databricks Automate Everything: You will develop robust CI/CD pipelines using GitHub Actions to manage the entire lifecycle of our Databricks assets—from infrastructure and clusters to the deployment and testing of dbt transformation workloads. WHAT IS OUR STACK? Data Platform: Azure Databricks, dbt, Delta Lake, ML/AI workflows on Databricks, Unity Catalog, and Apache Spark (PySpark). Cloud & IaC : Microsoft Azure, Terraform, Azure Data Lake Storage (ADLS) Gen2, Azure Key Vault CI/CD & Automation: GitHub Actions, Databricks CLI/APIs and Databricks Asset Bundles Microservices based on Node.js/Typescript, Kotlin and Python Infrastructure based on Azure ecosystem, Kubernetes, & Docker API technologies such as REST and GraphQL Event-driven architecture Angular (Micro) Frontends (TypeScript, Tailwind, NgRx, Nx, Jest) Monitoring & Alerting, e.g. Instana Product Usage Tracking using Amplitude & Azure Log Analytics WHO ARE WE LOOKING FOR? We are looking for a seasoned platform engineer with a deep specialization in building and administering large-scale data platforms. You are passionate about automation, governance, and enabling others through robust infrastructure. Core Requirements: Live by our engineering values Expert-level knowledge of Azure Databricks administration, including workspace setup, cluster management and policies, security best practices and cost optimization. Proven, hands-on mastery of Terraform. You should be able to manage a complex, multi-region Databricks environment entirely as code. Strong data engineering fundamentals, including deep experience with Apache Spark performance tuning, Delta Lake optimization (Z-ORDER, partitioning), and understanding data processing patterns. Practical experience designing or implementing platforms aligned with federated Data Management principles. A deep understanding of Unity Catalog for central governance and data discovery is essential. Solid experience building CI/CD pipelines for data and infrastructure (DataOps), preferably using GitHub Actions, to manage the lifecycle of Databricks assets. Deep understanding of core Azure services and how they integrate with Databricks Experience with data quality frameworks including unit testing, data validation, expectation-based testing ( DBT Expectations), dbt testing, and scalable automated testing pipelines. Additionally: Solid experience in data platform engineering, infrastructure, or SRE roles, with at least 4 years of deep, hands-on experience with Databricks. Experience managing large-scale, multi-region cloud environments. Open communication style and fluent written and spoken English skills are required At SAP LeanIX Product and Engineering, we embrace a hybrid remote work model, combining the benefits of in-person collaboration with the flexibility to work from home. We hire within commuting distance to our hubs in Bonn, Berlin, and Dresden, expecting employees to come to the office multiple times per week