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2 weeks ago
We seek a skilled Senior AWS Data Engineer to design, develop and maintain robust ETL/ELT pipelines on AWS using Spark and PySpark.
This role involves optimizing large-scale data processing workflows for performance and reliability. The successful candidate will work with AWS services such as Glue, EMR, S3, Lambda and Redshift.
Required Qualifications- 6+ years of experience in data engineering
- Strong proficiency in Spark, PySpark, SQL and Python
- Hands-on experience with AWS data services
- Solid understanding of distributed computing and data architecture
- Excellent problem-solving and communication skills
- Experience with CI/CD for data pipelines
- Familiarity with data lake and data warehouse architectures
- Design and Develop ETL/ELT Pipelines: Utilize Spark and PySpark to create efficient ETL/ELT pipelines on AWS.
- Optimize Data Processing Workflows: Ensure high-performance and reliable large-scale data processing workflows.
- Work with AWS Services: Leverage AWS services like Glue, EMR, S3, Lambda, and Redshift to meet business needs.
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