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Job Summary:
We are seeking a talented and experienced AWS Data Engineer to join our dynamic data team. In this role, you will be responsible for designing, building, optimizing, and maintaining our data pipeline and data fabric architecture on the AWS platform. You will work closely with data scientists, analysts, software engineers, and business stakeholders to understand data requirements and deliver high-quality, reliable data solutions that support critical business initiatives.
Key Responsibilities:
Design, build, and maintain scalable and reliable ETL/ELT pipelines using AWS services such as AWS Glue, Lambda, Step Functions, EMR, Kinesis, and others.
Develop and manage data warehouse and data lake solutions using Amazon Redshift, S3, Lake Formation, and Athena.
Implement data modeling best practices for both relational and non-relational data stores (e.g., RDS, DynamoDB, Aurora).
Optimize data pipeline performance, reliability, and cost-effectiveness within the AWS ecosystem.
Implement and manage data quality checks, monitoring, and alerting systems (e.g., using CloudWatch) to ensure data accuracy and pipeline health.
Write clean, maintainable, and efficient code, primarily in Python or Go.
Utilize Infrastructure as Code (IaC) principles and tools (e.g., CloudFormation, Terraform) to manage AWS resources.
Collaborate with data scientists and analysts to productionize models and provide necessary data infrastructure.
Ensure data security and compliance standards are met within the AWS environment.
Document data pipelines, architectures, and processes.
Stay up-to-date with the latest AWS data services and big data technologies.
Required Qualifications:
Bachelor's degree in Computer Science, Engineering, Information Technology, or a related field (or equivalent practical experience).
4 years of hands-on experience in a data engineering role.
Proven experience designing, building, and operating data pipelines and data warehouses within the AWS cloud environment.
Strong proficiency with core AWS data services: S3, Redshift, Glue, EMR, Lambda, Kinesis, RDS/Aurora, Athena.
Expertise in SQL and experience with data modeling techniques.
Proficiency in at least one programming language relevant to data engineering, preferably Python or Go.
Experience with big data technologies (e.g., Spark, Hadoop ecosystem).
Understanding of ETL/ELT concepts and best practices.
Excellent problem-solving and analytical skills.
Strong communication and collaboration skills.
