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Our client in the motor industry is looking to employ a Senior AWS Data Engineer. As a Big Data Engineer, you will be responsible for building and maintaining robust Big Data Pipelines using our client’s Data Platforms.
You will serve as a custodian of data, ensuring that it is shared securely and in compliance with information classification requirements on a need-to-know basis.Collaborating with cross-functional teams to understand data requirements and develop scalable solutions.Developing technical documentation and artifacts to support data engineering processes. Utilizing your expertise in Terraform, Python 3x, SQL , PySpark, ETL, Docker, Linux/Unix, and other relevant technologies to optimize data workflows. Leveraging AWS services such as S3, RDS, DynamoDB, Glue, and Data Pipeline for building and managing data pipelines. Implementing software design patterns and best practices to ensure scalability, reliability, and maintainability of data solutions.Proficiency in Terraform, Python 3x, SQL , PySpark, Boto3, ETL, Docker, Linux/Unix, and Big Data technologies.Strong understanding of AWS Cloud services with relevant certifications such as AWS Certified Cloud Practitioner, AWS Certified SysOps Associate, AWS Certified Developer Associate, AWS Certified Architect Associate, or AWS Certified Architect Professional.Ability to develop technical documentation and artifacts.Experience with Data Quality Tools like Great Expectations.Familiarity with AWS Glue, Data Pipeline, and other similar platforms for building data pipelines.Exceptional analytical skills for analyzing large and complex datasets.Preferred certifications: AWS Certified Cloud Practitioner, AWS Certified SysOps Associate, AWS Certified Developer Associate, AWS Certified Architect Associate, AWS Certified Architect Professional, or HashiCorp Certified Terraform Associate.Hands-on experience with AWS components and services.Experience in building data pipelines using AWS Glue or Data Pipeline.Strong understanding of various software design patterns and best practices.
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