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Data Engineer @
2 weeks ago
- Experience- 4 years and more
- Expertise in Python – advanced knowledge of Python, including libraries like pandas, numpy, etc., and data processing tools.
- Experience with PySpark – hands-on experience with Apache Spark and its integration with large-scale data processing systems.
- Experience with ETL and data pipelines – designing, implementing, and optimizing ETL processes in cloud or on-premises environments.
- Experience with cloud platforms - Azure
- SQL proficiency – solid experience working with relational databases (e.g., PostgreSQL, MySQL, SQL Server).
- Experience with Jupyter notebooks – using Jupyter for prototyping and testing data transformation processes.
- Understanding of data architecture (Data Fabric) – knowledge of building data infrastructure and integrating multiple data sources across the organization.
- Analytical skills – ability to solve complex problems and optimize data processing workflows.
- Collaboration and communication skills – ability to work effectively in a cross-functional team and communicate with various stakeholders.
