Data Engineer
Must Have Technical/Functional Skills
Snowflake: Deep expertise in Snowflake
PySpark: Strong hands-on experience using Apache Spark with Python for distributed data processing and transformation.
Database & SQL Knowledge: Advanced proficiency in Teradata
Roles & Responsibilities
Pipeline Development: Design and implement robust ETL/ELT pipelines using PySpark and SQL to ingest data from diverse sources including APIs, flat files, and relational databases
Data Modeling: Develop and manage complex data models (e.g., Star/Snowflake schemas) and maintain Fact and Dimension tables within Snowflake
Performance Optimization: Monitor and tune Snowflake queries and Spark jobs to optimize performance, reduce latency, and manage computational costs
Data Quality & Integrity: Implement automated data validation frameworks and testing procedures to ensure a "single source of truth" and high data reliability
Operations: Troubleshoot production pipeline issues, manage version control via Git
Education
Engineering
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