Description
Required Skills:
• Proficiency in AWS services and architectures, with a solid understanding of cloud best practices.
• Experience in programming languages such as Python or Java, along with a strong grasp of CI/CD principles. Knowledge of security and compliance standards within cloud environments.
• Problem-solving skills and a proactive approach to overcoming technical challenges.
• Proficiency in Python, PySpark, and AWS. A deep understanding of data privacy, security, and governance.
• Deep understanding of data systems, landscapes, policies, security standards, and governance. Understanding of Gen AI engineering setup.
• Proficient in software design, architecture, and implementation of real-time distributed systems on AWS.
• Skilled in AWS components and data processing (e.g., ECS, ECR, DynamoDB, Kinesis, S3, Lambda, AWS Glue, Redshift, AWSBatch).
• Experience with non-AWS CI/CD technologies (Github, Docker, Linux, Airflow, MLFlow and Terraform).
• Extensive knowledge of SQL, Python/PySpark, including developing and improving libraries.
• Experience with MLOps principles and tools (model & data lineage, observability, feature stores, model registries.
• Proficiency in AWS services and architectures, with a solid understanding of cloud best practices.
• Experience in programming languages such as Python or Java, along with a strong grasp of CI/CD principles. Knowledge of security and compliance standards within cloud environments.
• Problem-solving skills and a proactive approach to overcoming technical challenges.
• Proficiency in Python, PySpark, and AWS. A deep understanding of data privacy, security, and governance.
• Deep understanding of data systems, landscapes, policies, security standards, and governance. Understanding of Gen AI engineering setup.
• Proficient in software design, architecture, and implementation of real-time distributed systems on AWS.
• Skilled in AWS components and data processing (e.g., ECS, ECR, DynamoDB, Kinesis, S3, Lambda, AWS Glue, Redshift, AWSBatch).
• Experience with non-AWS CI/CD technologies (Github, Docker, Linux, Airflow, MLFlow and Terraform).
• Extensive knowledge of SQL, Python/PySpark, including developing and improving libraries.
• Experience with MLOps principles and tools (model & data lineage, observability, feature stores, model registries.