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An AWS Data Engineer specializes in designing, constructing, integrating, and maintaining the architecture (such as databases and large-scale processing systems), pipelines, and data sets that data analysts and data scientists use for their analyses and data mining. They often use Amazon Web Services' (AWS) extensive suite of tools and services for their operations.
Anicalls data engineers are specializes in designing and implementing large-scale data processing systems using services like AWS Glue, AWS Redshift, and AWS Kinesis.
Design, construct, install, and maintain large-scale processing systems and other infrastructure. Use AWS services like Amazon RDS, Redshift, and DynamoDB.
Implement and maintain the ETL (Extract, Transform, Load) process, leveraging AWS Glue or Data Pipeline for automating data flow between various AWS services and on-premises data sources.
Use AWS big data tools, such as Amazon EMR, for processing vast amounts of data.
Ensure systems meet business requirements and industry practices for data quality, reliability, and performance speed.
Use AWS Step Functions or Amazon SWF for visual coordination of distributed data workflows.
Implement real-time data processing and analytics using tools like AWS Lambda and Amazon Kinesis.
Design and implement scalable storage solutions using AWS storage services such as Amazon S3, EFS, and FSx.
Ensure the security of data solutions, implementing access controls, encryption at rest and in transit, and compliance monitoring using AWS tools like IAM, KMS, and Macie.
Monitor and manage costs associated with all the utilized AWS data services, ensuring the most cost-effective solutions are implemented.