Data Analytics Engineer - SAP DS Admin

Job description

**L35 - Software Engineer II** **– SAP Datasphere (Admin) | 4–6 Years** # **DT-US USI PxE Enterprise Platform Services (EPS): AI & Data** Role Overview: We are seeking a Data Engineer with 4–6 years of experience and strong hands-on expertise in SAP Datasphere administration. The role will focus on administering and operating Datasphere environments, supporting data integration and modeling, enabling secure access/governance, and collaborating with functional and technical teams to deliver reliable data products. knowledge of SAP Business Data Cloud (BDC) **Key Responsibilities:** - Embrace and drive a culture of accountability for customer and business outcomes. Develop quality engineering solutions that solve complex problems with valuable outcomes, ensuring high-quality test automations. - Serve as the quality advocate for products, ensuring high-quality automation coverage, appropriateness, feasibility, and alignment with business and customer goals. Design, develop, and maintain advanced automation frameworks to drive *“Automation first mindset”* using modern tools and technologies to streamline and enhance the testing process. - Maintain accountability for the integrity of test design, test automation, their ongoing maintenance and scale, as well as the quality of solutions. Stay hands-on, self-driven, and continuously learn new approaches, tools, techniques, and frameworks. Integrate modern tools and techniques into existing testing processes to improve accuracy, efficiency, and coverage of automated tests. - Develop lean test automation solutions through rapid, inexpensive experimentation to solve customer needs. Engage with customers and product teams before, during, and after delivery to ensure the right solution is delivered at the right time. - Adopt a mindset that favors action and evidence over extensive planning. Utilize a leaning-forward approach to navigate complexity and uncertainty, delivering lean, supportable, and maintainable solutions. - Work collaboratively with empowered, cross-functional teams including product management, experience, engineering, and delivery. Integrate diverse perspectives to make well-informed decisions that balance feasibility, viability, usability, and value. Foster a collaborative environment that enhances team synergy and innovation. - Possess basic knowledge of modern software and quality engineering practices and principles, including Agile methodologies and DevSecOps to deliver daily product deployments using techniques like fully automated in-sprint testing to accept the stories and work products, throughout the SDLC lifecycle. Strive to be a role model, leveraging these techniques to optimize solutioning and product delivery. Demonstrate an understanding of the full lifecycle product development, focusing on continuous improvement and learning. - Quickly acquire domain-specific knowledge relevant to the business or product. Translate business/user needs and UX/UI designs into test automation. Be a valuable, flexible, and dedicated team member, supportive of teammates, and focused on quality and tech debt payoff. - Exhibit strong communication skills, capable of articulating complex technical concepts clearly and compellingly. Support teammates and product teams through well-structured arguments and trade-offs supported by evidence. Create coherent narratives that align technical solutions with business objectives. - Engage and collaborate with product engineering teams, including customers as needed. Build and maintain constructive relationships, fostering a culture of co-creation and shared momentum towards achieving product goals. Align diverse perspectives and drive consensus to create feasible solutions. - Administer SAP Datasphere tenants and landscapes (configuration, monitoring, housekeeping). - Manage users, roles, authorizations, and security integration; enforce governance and access controls. - Configure and operate connections (e.g., SAP S/4HANA, SAP BW/4HANA, SAP HANA, cloud sources) and support connectivity troubleshooting. - Support data ingestion and orchestration (scheduling, monitoring, reruns, error handling, performance tuning). - Assist with data modeling in Datasphere (spaces, objects, semantic models) and promote reusable data products. - Implement and maintain transport/change management across environments (DEV/TEST/PROD), following release governance. - Establish operational practices: alerts, SLAs, runbooks, and incident/problem management. - Support data quality and reconciliation checks; collaborate on root-cause analysis for pipeline failures. - Provide guidance to developers/analysts on Datasphere standards, naming conventions, and best practices. **Required Qualifications** - 4–6 years in data engineering / data platform operations with at least 1–2 years hands-on SAP Datasphere administration. - Strong understanding of tenant/space administration, connectivity, monitoring, and troubleshooting in Datasphere. - Experience with role-based access control (RBAC) and security concepts (least privilege, segregation of duties). - Working knowledge of SAP BDC (Business Data Cloud) concepts and operational troubleshooting. - Solid fundamentals in SQL and data warehousing concepts (dimensional modeling, transformations, performance). - Familiarity with operational processes: incident management, change management, and documentation (runbooks). **Preferred / Nice-to-Have** - Experience with SAP Data Services (BODS), SAP SLT, SAP BW/4HANA, or SAP HANA administration. - Exposure to SAP Integration Suite, SAP Data Intelligence, or cloud data platforms (e.g., AWS/Azure/GCP). - Knowledge of data governance practices (cataloging, lineage, access reviews). - Scripting/automation for operations (e.g., Python, shell) and CI/CD familiarity. **Key Skills** - SAP Datasphere administration, monitoring, transport governance - Connectivity & integration troubleshooting - SQL, data modeling fundamentals - Access c