Data Engineer

• Build and maintain reliable data pipelines from SAP S/4HANA into Snowflake, ensuring clean, consistent, business-ready data for the global controlling and analytics team.

• Model, transform, and optimize data in Snowflake using strong SQL, structured layers, semantic models, and performance-aware data-engineering practices.

• Partner with business controllers and global stakeholders to convert requirements into MVPs, functional testing, UAT, rollout, and ongoing enhancements across 2–3 month project cycles.

• Support Power BI as the reporting and visualization front-end, including datasets, dashboards, calculations, and validation of outputs against source systems.

• Work through Jira/ticket-based delivery while communicating clearly with teams across India, Germany, Czech Republic, China, and external partners.

Ideal Candidate Profile

• 3–5 years of data engineering, analytics engineering, or BI engineering experience; no freshers/newcomers for this role.

• Strong hands-on Snowflake experience is the top priority, including data modeling, transformations, warehouse concepts, and performance optimization.

• Advanced SQL and practical ETL/ELT or data-pipeline experience, ideally around business, finance, controlling, operations, or manufacturing data.

• SAP S/4HANA exposure is a strong advantage but trainable; candidates with strong Snowflake/data-engineering fundamentals should still be considered if SAP depth is emerging.

• Power BI experience is helpful for front-end visualization, but should not outweigh Snowflake/data-engineering strength.

  • Computer Science or Information Systems background preferred; Snowflake Cortex, AI/ML on Snowflake, or chatbot-over-business-data exposure is a bonus signal.