We are seeking an experienced Data Engineer to design and optimize ETL/ELT pipelines for migrating and transforming data from SAP to Snowflake. The role involves developing scalable data models, collaborating with cross-functional teams, ensuring data quality, and optimizing performance in a cloud data warehouse environment.
Responsibilities:
Design, develop, and optimize ETL/ELT pipelines to migrate and transform data from SAP to Snowflake.
Develop and maintain scalable data models (fact and dimension tables) within Snowflake to support analytical use cases.
Collaborate with SAP, AtScale, and Power BI teams to ensure seamless data flow across the platform.
Write and optimize SQL queries in Snowflake for performance, scalability, and data integrity.
Ensure data quality and consistency in the Snowflake data warehouse.
Work with stakeholders to understand data requirements and ensure alignment between data architecture and business goals.
Continuously monitor and tune data performance, troubleshooting issues as needed.
Requirements:
5+ years of experience as a Data Engineer, with 3+ years of hands-on experience in Snowflake.
Expertise in SQL, Snowflake Architecture, and Snowflake best practices (e.g., data clustering, partitioning, etc.).
Experience working with ETL/ELT tools and integrating data from multiple sources (preferably SAP).
Strong knowledge of data pipelines, data integration, and cloud data platforms.
Familiarity with data modeling principles and best practices for building data warehouses.
Strong problem-solving skills and experience in optimizing large datasets for query performance.
Data Engineering, Snowflake, SQL, Snowflake Architecture, Snowflake Best Practices, ETL/ELT, SAP, Data Pipelines, Data Integration, Cloud Data Platforms, Data Modeling, Data Warehousing, Performance Optimization, Troubleshooting, Data Quality