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3 days ago
We are seeking a highly skilled data professional to lead our team in designing and implementing scalable data pipelines using AWS services.
The ideal candidate will have expertise in building robust ETL/ELT workflows using Spark, PySpark, SQL, and Python, along with hands-on experience in the AWS ecosystem.
Key Responsibilities:- Design, develop, and maintain large-scale data processing workflows on AWS for performance and reliability.
- Work with key AWS services including Glue, EMR, S3, Lambda, and Redshift.
- Ensure data quality, governance, and security across all data pipelines.
- 6+ years of experience in data engineering with a focus on scalability and reliability.
- Strong proficiency in Spark, PySpark, SQL, and Python programming languages.
- Hands-on experience with AWS data services including Glue, EMR, S3, Lambda, and Redshift.
- Solid understanding of distributed computing and data architecture principles.
- Excellent problem-solving and communication skills with ability to collaborate with cross-functional teams.
- Experience with CI/CD pipeline management for data workflows.
- Familiarity with data lake and data warehouse architectures.
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