Found Description
4–7 years of total experience in Data engineering and big data pipeline development
Demonstrated experience in Snowflake and DBT
Experience with big data processing frameworks and modern data architecture principles
Advanced proficiency in SQL, Python, and PySpark for scalable data processing and transformation
Hands-on experience in building end-to-end ETL/ELT pipelines using DBT.
Strong grasp of data warehousing, lakehouse architecture, and modern analytics on cloud platforms
Hands-on experience with large-scale data platforms and performance tuning for high-volume data pipelines
Well-versed in DevOps practices, Git, and CI/CD pipelines for automating data engineering workflows
Strong understanding of modern data architecture and governance frameworks in a cloud environment
Proficiency in Tableau and BI tools with experience in building scalable dashboards and optimizing data models
Basic knowledge of SAP data models
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