AWS Data Engineer
2 months ago
Job Description :
- Develop, deploy, and maintain robust ETL pipelines using Python and PySpark to process large-scale datasets efficiently.
- Utilize PySpark to perform complex data transformations and processing tasks, ensuring data accuracy and quality.
- Write and optimize advanced SQL queries to extract, manipulate, and analyze data from relational databases.
- Leverage AWS services including AWS Glue, Lambda, and others to design and implement scalable data solutions.
- Create and manage data models and warehouse solutions, ensuring efficient data storage and retrieval.
- Identify and resolve data processing issues, optimizing pipelines and queries for performance and reliability.
- Work closely with cross-functional teams to understand data requirements and deliver actionable insights.
- Communicate technical concepts clearly to non-technical stakeholders.
- Documentation : Maintain comprehensive documentation of data workflows, pipelines, and processes.
Qualifications :
- 6+ years of professional experience in Python development with a strong focus on data processing and ETL.
- Proficiency in Python and PySpark for large-scale data processing, advanced SQL skills with experience in relational databases.
- Hands-on experience with AWS Glue, Lambda, and other related AWS services.
- Solid understanding of data engineering principles, data warehousing, and data modeling
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