This role focuses on leading the design and development of advanced SAP Cloud Analytics solutions. The Staff Engineer will drive the implementation of data strategies to meet diverse business requirements and ensure robust data management.

Key to this position is collaboration with various teams to understand and address data needs. The engineer will be instrumental in optimizing data models and ETL processes, ensuring efficient data integration and reporting capabilities.

This position also involves mentoring junior engineers and providing technical guidance. Maintaining data accuracy, integrity, and security within SAP environments is paramount. The role requires active participation in project planning and monitoring, alongside performance tuning and troubleshooting.

Lead the design and development of SAP Cloud Analytics solutions tailored to specific business needs.

Collaborate effectively with cross-functional teams to define and analyze data requirements, aligning them with organizational objectives.

Develop and refine data models and ETL processes for seamless data integration and impactful reporting.

Mentor junior data engineers, fostering their growth and enhancing the team's overall technical proficiency.

Uphold data accuracy, integrity, and security standards within SAP ecosystems.

Engage in project planning and management, ensuring timely delivery of all project milestones and outcomes.

Monitor system performance, proactively identify and resolve issues, and implement necessary enhancements.

Stay abreast of the latest SAP technologies and industry best practices, championing their adoption.

A strong foundation in SAP Cloud Analytics is essential for this role.

Proven ability to collaborate with diverse teams and translate business requirements into technical data solutions.

Experience in developing and optimizing data models and ETL processes is crucial.

Demonstrated leadership and mentoring capabilities are expected.

A commitment to ensuring data quality, integrity, and security is required.

Familiarity with project planning and management methodologies is beneficial.

Skills in system performance monitoring and troubleshooting are necessary.

Continuous learning and advocacy for industry best practices in data engineering are highly valued.