Posted:1 day ago|
Platform:
Hybrid
Full Time
• Design, develop, and maintain scalable and reliable data pipelines using AWS / Azure services, PySpark, and Databricks.
• Collaborate with cross-functional teams to understand data requirements, identify data sources, and define data ingestion strategies. • Implement data extraction, transformation, and loading (ETL) processes to enable efficient data integration from various sources. • Hands-on experience in developing and optimizing Databricks data pipelines using PySpark. • Proficient in SQL, Python, and ETL processes • Optimize and tune data pipelines to ensure high performance, scalability, and data quality. • Monitor and troubleshoot data pipelines to identify and resolve issues in a timely manner. • Collaborate with data scientists and analysts to provide them with clean, transformed, and reliable data for analysis and modeling. • Develop and maintain data documentation, including data lineage, data dictionaries, and metadata management. • Level of exp in Databricks: E4 • Should have worked in different functional perimeters (e.g. finance, HR, Geology, HSE)
CGI
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