AWS Data Engineer
1 month ago
Role and Responsibilities :
- Data Engineering : Design, develop, and implement data pipelines and ETL processes using AWS services like Glue, Python, Redshift, and Spark.
- Data Warehousing : Build and maintain data warehouses and data lakes on AWS.
- Data Migration : Migrate data from legacy systems to AWS cloud platforms.
- Data Governance : Implement data governance policies and best practices to ensure data quality and security.
- ETL Development : Develop ETL workflows using tools like Glue and Python.
- Data Transformation : Transform data using SQL, Python, and other programming languages.
- Data Analysis : Analyze data using SQL, Python, and data visualization tools.
- DevOps : Implement DevOps practices for data engineering, including CI/CD pipelines and infrastructure automation.
- Cloud Architecture : Design and implement cloud architectures for data processing and analytics on AWS.
Required Qualifications :
- 6-8 years of experience in data engineering or a related field.
- Strong proficiency in Python and SQL.
- Experience with AWS data services like Glue, Redshift, and Spark.
- Knowledge of ETL processes and data warehousing concepts.
- Experience with data migration and data transformation.
- Understanding of data governance and data quality best practices.
- Experience with DevOps tools and practices.
- Strong analytical and problem-solving skills.
- Excellent communication and collaboration skills.
Preferred Qualifications :
- Experience with Airflow for workflow orchestration.
- Knowledge of machine learning and data science techniques.
- Certifications in AWS data engineering or related fields
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